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A | Foundations of Machine Learning

aims at strengthening the competence in Statistical Foundations and Explainability, Mathematical Foundations, and Computational Methods. These fields form the basis for all methodological advances.

MCML @Google Scholar

A1 | Statistical Foundations & Explainability

Research is being conducted at MCML to improve the reliability, interpretability, and acceptability of results obtained with ML algorithms for their practical application through better integration of statistical concepts. Key challenges include the integration of uncertainty quantification into ML algorithms, the explainability of ML models, the simplification of ML methods, and the incorporation of prior knowledge into ML algorithms.

Stefan Bauer

Prof. Dr.

Core PI

Algorithmic Machine Learning & Explainable AI

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

Anne-Laure Boulesteix

Prof. Dr.

Core PI

Biometry in Molecular Medicine

Andreas Döpp

Dr. habil

Collaborating PI

Data-driven methods in Physics and Optics

Mathias Drton

Prof. Dr.

Core PI

Mathematical Statistics

Stefan Feuerriegel

Prof. Dr.

Core PI

Artificial Intelligence in Management

Vincent Fortuin

Dr.

Collaborating PI

Bayesian Deep Learning

Debarghya Ghoshdastidar

Prof. Dr.

Core PI

Theoretical Foundations of Artificial Intelligence

Gjergji Kasneci

Prof. Dr.

Core PI

Responsible Data Science

Göran Kauermann

Prof. Dr.

Core PI

Applied Statistics in Social Sciences, Economics and Business

Thomas Nagler

Prof. Dr.

Core PI

Computational Statistics & Data Science

David Rügamer

Prof. Dr.

Core PI

Statistics, Data Science and Machine Learning

Fabian Scheipl

PD Dr.

Core PI

Functional Data Analysis

Volker Schmid

Prof. Dr.

Core PI

Bayesian Imaging & Spatial Statistics

Michael Schomaker

Prof. Dr.

Collaborating PI

Biostatistics

©all images: LMU | TUM

Publications in Research Area A1

[741]

R. Ma • D. Geissler • S. Feuerriegel • T. Lauinger • D. McCoy • P. Wisniewski
Analyzing Social Media Claims regarding Youth Online Safety Features to Identify Problem Areas and Communication Gaps.
CSCW 2026 - 29th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. Salt Lake City, UT, USA, Oct 10-14, 2026. To be published. Preprint available. arXiv

[740]

T. Nagler • T. Brock • N. Palm
Online Bootstrap Inference for the Trend of Nonstationary Time Series.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[739]

R. D. Paul • A. Stratmann • J. F. Jadebeck • M. Beyß • H. Scharr • D. Rügamer • K. Nöh
Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[738]

V. Venkatesh • E. Hüllermeier • B. Bischl • M. Rezaei
Structured Credal Learning.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[737]

P. Janetzky • T. Schlagenhauf • M. Klar • S. Feuerriegel
Slowing Down Forgetting in Continual Learning: Evidence from Manufacturing.
KDD 2026 - 32nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Jeju Island, Republic of Korea, Aug 09-13, 2026. To be published.

[736]

D. Frauen • M. Brockschmidt • K. Hess • H. Ma • Y. Ma • A. Maarouf • M. Schröder • J. Schweisthal • Y. Wang • A. Deviyani • S. Parbhoo • R. G. Krishnan • S. Feuerriegel
Causal methods for LLM development and evaluation.
KDD 2026 - 32nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Jeju Island, Republic of Korea, Aug 09-13, 2026. To be published. Preprint available. arXiv

[735]

Y. Ma • Y. Huang • W. Wang • X. Luo • X. Zhang • S. Feuerriegel
Synthetic Interaction Data for Scalable Personalization in Large Language Models.
KDD 2026 - 32nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Jeju Island, Republic of Korea, Aug 09-13, 2026. To be published. Preprint available. arXiv

[734]

Y. Li • G. Kasneci
Safety Cost of Steering Vectors Is Separable and Reducible.
AI4GOOD @ICML 2026 - Workshop on Trustworthy AI for Good at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[733]

Y. Li • G. Kasneci
Safety Cost of Steering Vectors Is Separable and Reducible.
CompLearn @ICML 2026 - 2nd Workshop on Compositional Learning: Safety, Interpretability, and Agents at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[732]

E. Sommer • K. Diao • J. Robnik • U. Seljak • D. Rügamer
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. URL

[731]

M. Brockschmidt • M. Schröder • S. Feuerriegel
SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. Spotlight Presentation. To be published. Preprint available. URL

[730]

E. Sommer • D. Rügamer
Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. Spotlight Presentation. To be published. Preprint available. URL

[729]

D. Rundel • F. Fumagalli • M. Muschalik • B. Bischl • M. Feurer
ShaplEIG: Bayesian Experimental Design for Shapley Value Estimation.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. URL GitHub

[728]

M. Akhtar • A. Reuel • P. Soni • S. Ahuja • P. S. Ammanamanchi • R. Rawal • V. Zouhar • S. Yadav • C. Whitehouse • D. Ki • J. Mickel • L. Choshen • M. Šuppa • J. Batzner • J. Chim • J. Sania • Y. Long • H. A. Rahmani • C. Knight • Y. Nan • J. Raj • Y. Fan • S. Singh • S. Sahoo • E. Habba • U. Gohar • S. Pawar • R. Scholz • A. Subramonian • J. Ni • M. Kochenderfer • S. Koyejo • M. Sachan • S. Biderman • Z. Talat • A. Ghosh • I. Solaiman
When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[727]

E. Antipov • A. Palma • L. Consoli • S. Günnemann • A. Dittadi • F. J. Theis
Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[726]

H. Arno • D. Frauen • E. Javurek • T. Demeester • S. Feuerriegel
Rank-Learner: Orthogonal Ranking of Treatment Effects.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[725]

D. Frauen • A. Deviyani • M. van der Schaar • S. Feuerriegel
Nonparametric LLM Evaluation from Preference Data.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[724]

F. Fumagalli • L. Butler • J. S. Kang • K. Ramchandran • R. T. Witter
An Odd Estimator for Shapley Values.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. arXiv

[723]

Y. Huang • Z. Jiang • Y. Ma • Y. Jiang • X. Wang • Y. Zhou • Y. Hao • K. Guo • P.-Y. Chen • S. Feuerriegel • X. Zhang
ProbeLLM: Automating Principled Diagnosis of LLM Failures.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[722]

P. Janetzky • T. Schlagenhauf • S. Feuerriegel
Continual Learning of Domain-Invariant Representations.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[721]

F. Kapl • E. Angelis • K. Maile • J. von Oswald • S. Bauer
From Growing to Looping: A Unified View of Iterative Computation in LLMs.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[720]

F. Kapl • A. M. K. Mamaghan • M. Seitzer • K. H. Johansson • C. Marr • S. Bauer • A. Dittadi
Are Object-Centric Representations Better at Compositional Generalization?
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[719]

E. Kasneci • G. Kasneci
Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[718]

M. Li • Y. Ding • E. Garces Arias • C. Heumann
Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. arXiv

[717]

H. Ma • D. Frauen • S. Feuerriegel
DeepBlip: Estimating Conditional Average Treatment Effects Over Time.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[716]

V. Melnychuk • V. Balazadeh • S. Feuerriegel • R. G. Krishnan
Frequentist Consistency of Prior-Data Fitted Networks for Causal Inference.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[715]

P. Mortimer • C. Diaconu • T. Rochussen • B. Mlodozeniec • R. E. Turner
Incremental Transformer Neural Processes.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[714]

J. Odgers • B. Riegler • S. Swaroop • V. Fortuin
Gaussian Mean Field Variational Inference can Overestimate Predictive Variance.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[713]

T. Papamarkou • P. Alquier • M. Bauer • W. Buntine • A. Davison • G. K. Dziugaite • M. Filippone • A. Y. K. Foong • V. Fortuin • D. Fouskakis • J. Frellsen • E. Hüllermeier • T. Karaletsos • M. E. Khan • N. Kotelevskii • S. Lahlou • Y. Li • F. Liu • C. Lyle • T. Möllenhoff • K. Palla • M. Panov • Y. Sale • K. Schweighofer • A. Shelmanov • S. Swaroop • M. Trapp • W. Waegeman • A. G. Wilson • A. Zaytsev
Position: Agentic AI Orchestration Should Be Bayes-Consistent.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[712]

D. Rügamer
On the Epistemic Uncertainty of Overparametrized Neural Networks.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[711]

E. Valero-Leal • B. Bischl • P. Larrañaga • C. Bielza • G. Casalicchio
Optimal Transport Group Counterfactual Explanations.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[710]

R. T. Witter • Á. Parafita • T. Garriga • M. Muschalik • F. Fumagalli • A. Brando • L. Rosenblatt
Exactly Computing do-Shapley Values.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. arXiv

[709]

M. Zarvandi • M. Timothy • T. Wasserer • D. Ghoshdastidar
Interpretable Self-Supervised Learning via Representer Landmarks and Nyström Approximation.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[708]

Z. Zhang • S. Yang • B. Prenkaj • G. Kasneci
Active Tabular Augmentation via Policy-Guided Diffusion Inpainting.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[707]

V. Pauline • K. Tamogashev • A. Carter • S. Choi • S. Bauer • E. S. Whitammer
Amortised Inference through One-Step Implicit Sampling.
SPIGM @ICML 2026 - Workshop on Structured Probabilistic Inference and Generative Modeling at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. URL

[706]

M. Becker
rush: A Database-Centric Architecture for Distributed Computing in R.
useR! 2026 - International R User Conference. Warsaw, Poland, Jul 06-09, 2026. GitHub

[705]

Y. Ding • M. Li • E. Garces Arias • M. Aßenmacher • C. Heumann • C. Zhang
Min-k Sampling: Decoupling Truncation from Temperature Scaling via Relative Logit Dynamics.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI

[704]

A. Sarawgi • E. Garces Arias • C. Zotter
Digitizing Nepal's Written Heritage: A Comprehensive HTR Pipeline for Old Nepali Manuscripts.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI

[703]

F. Weeber • V. Neplenbroek • J. Batzner • S. Padó
One Persona, Many Cues, Different Results: How Sociodemographic Cues Impact LLM Personalization.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI

[702]

S. Yang • Z. Zhang • B. Prenkaj • G. Kasneci
SAGE: Sparse Adaptive Guidance for Dependency-Aware Tabular Data Generation.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI GitHub

[701]

C. Yuan • Z. Zhang • G. Kasneci
Where Paths Split: Localized, Calibrated Control of Moral Reasoning in Large Language Models.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI GitHub

[700]

Y. Li • A. Fastowski • E. Zaradoukas • B. Prenkaj • G. Kasneci
Analysing the Safety Pitfalls of Steering Vectors.
Findings @ACL 2026 - Findings at the 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI GitHub

[699]

C. Zhang • H. Wang • Z. Yu • E. Garces Arias • J. Rodemann • Z. Zhang • Q. Li • G. Fan • K. Muandet • C. Heumann
Self-Reinforcing Controllable Synthesis of Rare Relational Data via Bayesian Calibration.
Findings @ACL 2026 - Findings at the 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI GitHub

[698]

T. Heiß • C. Bögel • B. Bischl • G. Casalicchio
Analyzing Error Sources in Global Feature Effect Estimation.
xAI 2026 - 4th World Conference on Explainable Artificial Intelligence. Fortaleza, Brazil, Jul 01-03, 2026. To be published. Preprint available. arXiv

[697]

T. Nagler • S. Langer
Optimal neural network approximation of smooth compositional functions on sets with low intrinsic dimension.
COLT 2026 - 39th Annual Conference on Learning Theory. San Diego, CA, USA, Jun 29-Jul 03, 2026. To be published. Preprint available. arXiv

[696]

E. Sommer • K. Diao • J. Robnik • U. Seljak • D. Rügamer
Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
ISBA 2026 - 18th World Meeting of the International Society for Bayesian Analysis. Nagoya, Japan, Jun 28-Jul 03, 2026. Invited Talk. arXiv

[695]

L. Bothmann • P. A. Boustani • J. M. Alvarez • G. Casalicchio • B. Bischl • S. Dandl
Privilege Scores.
ACM FAccT 2026 - 9th ACM Conference on Fairness, Accountability, and Transparency. Montréal, Canada, Jun 25-28, 2026. To be published. Preprint available. arXiv

[694]

S. Feuerriegel • C. Barrie • M. J. Crockett • L. K. Globig • K. L. McLoughlin • D.-M. Mirea • A. Spirling • D. Yang • T. Althoff • M. Antoniak • L. P. Argyle • A. Ashokkumar • M. Atari • H. Bailey • K. Bauer • U. Bhatt • Y. Chai • T. Chakraborty • Y. Chandra • H. Chen • H. Daumé III • G. De Francisci Morales • M. Dehghani • D. Dillion • J. C. Eichstaedt • K. Forster • D. Geissler • K. Gray • T. L. Griffiths • J. Hartmann • O. P. Hauser • J. K. He • R. Hemrajani • F. Holzmeister • A. H.-C. Hwang • T. Hu • A. A. Ivanova • N. Köbis • Y. Kyrychenko • H. Lakkaraju • J. Liu • A. Maarouf • S. Maier • L. Meincke • R. Mihalcea • B. Mittelstadt • S. M. Mohammad • M. Naaman • O. Netzer • A. Oh • D. C. Ong • F. Pierri • B. Plank • I. Rahwan • T. Rahwan • P. S. B. Rao • C. E. Robertson • D. M. Rothschild • M. J. Salganik • E. Schulz • C. Shah • Y. R. Shrestha • E. Shutova • A. A. Siegel • A. Simchon • H. Sun • M. Toetzke • J. J. Van Bavel • M. Vaccaro • J. W. Vaughan • E. Vayena • P. O. S. Vaz-de-Melo • B. Vecchione • A. Wang • R. West • R. Willer • D. U. Wulff • R. Zhang • S. Zhang • S. Rathje • M. H. Ribeiro
A reporting checklist for large language models in behavioural science.
Nature Human Behaviour. Jun. 2026. PDF URL

[693]

M. Becker • B. Bischl
rush: Scalable Asynchronous Distributed Computing via Shared State in R.
Preprint (Jun. 2026). arXiv

[692]

A. Bashardoust • Y. Feng • D. Geißler • S. Feuerriegel • Y. R. Shrestha
The Effect of Education in Prompt Engineering: Evidence from Journalists.
ICWSM 2026 - 20th International AAAI Conference on Web and Social Media. Los Angeles, CA, USA, May 27-Jun 29, 2026. To be published. Preprint available. arXiv

[691]

Y. Feng • S. Feuerriegel • Y. R. Shrestha
Contextualizing Recommendation Explanations with LLMs: A User Study.
ICWSM 2026 - 20th International AAAI Conference on Web and Social Media. Los Angeles, CA, USA, May 27-Jun 29, 2026. To be published. Preprint available. arXiv

[690]

H. Funk • C. Gruber • G. Kauermann • H. Küchenhoff • R. Ludwig • M. Mittermeier
Uncertainty-Aware AI Forecasting of European Droughts: The Role of Internal Climate Variability.
EGU 2026 - General Assembly of the European Geosciences Union. Vienna, Austria, May 03-08, 2026. DOI

[689]

V. Melnychuk • D. Frauen • J. Schweisthal • S. Feuerriegel
Orthogonal Representation Learning for Estimating Causal Quantities.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. Oral Presentation. To be published. Preprint available. arXiv

[688]

J. Kobialka • E. Sommer • J. Kwon • D. Dold • D. Rügamer
On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. Spotlight Presentation. To be published. URL

[687]

R. Schulte • D. Rügamer
Rethinking Intrinsic Dimension Estimation in Neural Representations.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. URL

[686]

F. Bleile • S. Lumpp • M. Drton
Efficient Learning of Stationary Diffusions with Stein-type Discrepancies.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. Preprint available. arXiv

[685]

T. Pielok • B. Bischl • D. Rügamer
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. Preprint available. arXiv

[684]

M. Schlager • E. Sommer • T. Möllenhoff • D. Rügamer
Guiding Posterior Exploration with Optimizer-Derived Geometry.
OPTIMAL @AISTATS 2026 - Workshop on Optimisation and Post-Bayesian Inference in Machine Learning at the 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. GitHub

[683]

E. Sommer • R. Schulte • S. Deubner • J. Kobialka • D. Rügamer
Towards E-Value Based Stopping Rules for Bayesian Deep Ensembles.
OPTIMAL @AISTATS 2026 - Workshop on Optimisation and Post-Bayesian Inference in Machine Learning at the 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. Preprint available. arXiv GitHub

[682]

T. Müller • R. Hornung • S. Szymczak • H. Buchner
ShadowVIMP: permutation-based multiple testing-controlled variable selection.
BMC Bioinformatics 27.96. May. 2026. DOI

[681]

P. Garthen • H. S. C. Mudragada • S. Schwarz • . Edelhoff • M. J. Steinbauer • W. Peters • K. Kuecuekaytekin • L. Bothmann
Distance-based population density estimates from camera traps: Strong impact of technical choices in automated pipelines.
Ecological Informatics 95.103682. May. 2026. DOI

[680]

R. Niedermeier • N. Castelletti • A. Bender • Hoelscher • O. Ivanova
Interpretations of Menstrual Blood Appearance and Diagnostic Potential Among Social Media Users: Cross-Sectional Mixed Methods Social Media Listening Study.
Journal of Medical Internet Research 28. May. 2026. DOI

[679]

V. Arvanitis • A. Aslanidis • E. Sommer • D. Rügamer
bde: A Python Package for Bayesian Deep Ensembles via MILE.
Preprint (May. 2026). arXiv GitHub

[678]

H. Baniecki • P. Biecek • F. Fumagalli
Attributions All the Way Down? The Metagame of Interpretability.
Preprint (May. 2026). arXiv GitHub

[677]

M. Brockschmidt • S. M. A. R. Thies • M. Schröder • D. Frauen • V. Melnychuk • M. Muschalik • E. Hüllermeier • S. Feuerriegel
ConfoundingSHAP: Quantifying confounding strength in causal inference.
Preprint (May. 2026). arXiv

[676]

J. Büssing • M. Schlager • T. Heiß • T. Zehle • M. Feurer
MO-CAPO: Multi-Objective Cost-Aware Prompt Optimization.
Preprint (May. 2026). arXiv

[675]

A. Chatterjee • M. Schöffel • M. Aßenmacher • E. Garces Arias
Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan.
Preprint (May. 2026). arXiv GitHub

[674]

Y. Han • Y. Wang • D. Ghoshdastidar • J. Kinder
ALPHA: Active Learning with PAC-Bayesian Theory for Android Malware Detection.
Preprint (May. 2026). URL GitHub

[673]

S. Maier • M. Gunzenhäuser • J. Schweisthal • M. Schneider • S. Feuerriegel
A meta-analysis of the effect of generative AI on productivity and learning in programming.
Preprint (May. 2026). arXiv GitHub

[672]

M. Schröder • P. Janetzky • M. Klar • S. Feuerriegel
ORTHOBO: Orthogonal Bayesian Hyperparameter Optimization.
Preprint (May. 2026). arXiv

[671]

E. Garces Arias
A Credal-Set Perspective on Task-Induced Distributional Drift in Text Generation.
CAO @ICLR 2026 - Workshop Catch, Adapt, and Operate: Monitoring ML Models Under Drift at the 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[670]

C. Kolb
Advances in deep learning: differentiable sparsity, overparameterization, and semi-structured regression.
Dissertation LMU München. Apr. 2026. DOI

[669]

T. Höppe • S. Bauer • Q. Liu • A. Dittadi • K. Neklyudov
On Closed-Form Couplings.
GRaM @ICLR 2026 - Workshop on Geometry-grounded Representation Learning and Generative Modeling at the 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[668]

K. Hess • D. Frauen • V. Melnychuk • S. Feuerriegel
IGC-Net for conditional average potential outcome estimation over time.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[667]

K. Heß • D. Frauen • V. Melnychuk • S. Feuerriegel
Efficient and Sharp Off-Policy Learning under Unobserved Confounding.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[666]

K. Heß • D. Frauen • M. van der Schaar • S. Feuerriegel
Overlap-weighted orthogonal meta-learner for treatment effect estimation over time.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[665]

E. Javurek • V. Melnychuk • J. Schweisthal • K. Heß • D. Frauen • S. Feuerriegel
An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[664]

Y. Ma • D. Frauen • E. Javurek • S. Feuerriegel
Foundation Models for Causal Inference via Prior-Data Fitted Networks.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[663]

V. Melnychuk • S. Feuerriegel
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[662]

V. Melnychuk • D. Frauen • J. Schweisthal • S. Feuerriegel
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[661]

T. Rochussen • V. Fortuin
Amortising Inference and Meta-Learning Priors in Neural Networks.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[660]

E. Zaradoukas • B. Prenkaj • G. Kasneci
Reinforcement Unlearning via Group Relative Policy Optimization.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[659]

L. Eyring • V. Pauline • S. Bauer • A. Dosovitskiy • Z. Akata
DDNO: Discrete Diffusion Noise Optimization.
ReALM-GEN @ICLR 2026 - Workshop on Real‑World Constrained and Preference‑Aligned Flow‑ and Diffusion‑Based Models at the 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[658]

A. Mohgaonkar • L. Gosch • M. Sabanayagam • D. Ghoshdastidar • S. Günnemann
Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning.
Trustworthy AI @ICLR 2026 - Workshop on Principled Design for Trustworthy AI - Interpretability, Robustness, and Safety across Modalities at the 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv GitHub

[657]

D. Geissler • C. Robertson • S. Feuerriegel
Designing Effective Digital Literacy Interventions for Boosting Deepfake Discernment.
CHI 2026 - ACM CHI Conference on Human Factors in Computing Systems. Barcelona, Spain, Apr 13-17, 2026. DOI

[656]

S. Maier • M. Schneider • S. Feuerriegel
Partnering with Generative AI: Experimental Evaluation of Model-Led and Human-Led Interaction in Human-AI Co-Creation.
CHI 2026 - ACM CHI Conference on Human Factors in Computing Systems. Barcelona, Spain, Apr 13-17, 2026. DOI

[655]

M. Schimpf • S. Maier • A. Wyrowski • L. Christoforakos • S. Feuerriegel • T. Bohné
Supporting Effective Goal Setting with LLM-Based Chatbots.
CHI 2026 - ACM CHI Conference on Human Factors in Computing Systems. Barcelona, Spain, Apr 13-17, 2026. DOI

[654]

Y. Ma • V. Melnychuk • D. Frauen • S. Feuerriegel
Consistent End-to-End Estimation for Counterfactual Fairness.
CLeaR 2026 - 5th Conference on Causal Learning and Reasoning. Cambridge, MA, USA, Apr 06-08, 2026. To be published. Preprint available. URL GitHub

[653]

J. Zobolas • A.-M. George • A. López • S. F. Fischer • M. Becker • T. Aittokallio
Prognostic biomarker discovery in pancreatic cancer through hybrid ensemble feature selection and multi-omics data.
BioData Mining Early Access. Apr. 2026. DOI

[652]

L. Burk • J. Zobolas • B. Bischl • A. Bender • M. N. Wright • R. Sonabend
A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data.
Bioinformatics.btag186. Apr. 2026. DOI GitHub

[651]

C. Wiederkehr • C. Heumann • M. Schomaker
Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity.
Biometrical Journal 68.3. Apr. 2026. DOI

[650]

B. Pulido • A. M. Franco-Pereira • R. E. Lillo • F. Scheipl
Area-based epigraph and hypograph indices for functional outlier detection.
Computational Statistics 41.72. Apr. 2026. DOI

[649]

C. Kolb • C. L. Müller • B. Bischl • D. Rügamer
Smoothing the Edges: Smooth Optimization for Sparse Regularization Using Hadamard Overparametrization.
Machine Learning 115.87. Apr. 2026. DOI

[648]

P. Spitzer • D. Hendriks • J. Rudolph • S. Schläger • J. Ricke • N. Kühl • B. F. Hoppe • S. Feuerriegel
The effect of medical explanations from large language models on diagnostic accuracy in radiology.
npj Digital Medicine 9.333. Apr. 2026. DOI

[647]

S. Fischer • L. Burk • C. Zhang • B. Bischl • M. Binder
mlr3torch: A Deep Learning Framework in R based on mlr3 and torch.
Preprint (Apr. 2026). arXiv GitHub

[646]

K. Hess • D. Frauen • N. Kilbertus • S. Feuerriegel
Debiased neural operators for estimating functionals.
Preprint (Apr. 2026). arXiv

[645]

S. Jacob • B. Prenkaj • W. Shao • G. Kasneci
TabSCM: A practical Framework for Generating Realistic Tabular Data.
Preprint (Apr. 2026). arXiv GitHub

[644]

H. Ma • D. Frauen • V. Melnychuk • S. Feuerriegel
Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects.
Preprint (Apr. 2026). arXiv

[643]

S. Madadkhani • N. Sturma • M. Drton • S. Ikonnikova
Mapping the causal structure of price formation in Texas’s transitioning electricity market.
Preprint (Apr. 2026). arXiv

[642]

F. Steinbauer • E. Oswald • K. Kirchheim • B. Prenkaj • F. Kofler • G. Kasneci
Efficient General Intelligence through Multi-Component Integration.
Preprint (Apr. 2026). URL

[641]

D. Frauen
Causal machine learning for reliable decision-making.
Dissertation LMU München. Mar. 2026. DOI

[640]

T. Zehle • T. Heiß • M. Schlager • M. Aßenmacher • M. Feurer
promptolution: A Unified, Modular Framework for Prompt Optimization.
EACL 2026 - 19th Conference of the European Chapter of the Association for Computational Linguistics. Rabat, Morocco, Mar 24-29, 2026. DOI

[639]

T. Zehle • M. Aßenmacher
Can Calibration of Positional Encodings Enhance Long Context Utilization?
Findings @EACL 2026 - Findings of the 19th Conference of the European Chapter of the Association for Computational Linguistics. Rabat, Morocco, Mar 24-29, 2026. DOI

[638]

T. Pielok
Advancing variational inference: semi-implicit models, adaptive proposals, and Functional Stein Gradients.
Dissertation LMU München. Mar. 2026. DOI

[637]

W. H. Hartl • C. Stoppe • Y. Kotani • G. Landoni • A. G. Day • J. Piller • M. Neuberger • A. Bender
Study protocol for the use of propofol in adult intensive care unit patients: a secondary analysis of an extensive international database.
Critical Care Science 38. Mar. 2026. DOI

[636]

L. Benz • U. Pul • T. Brock • F. Schwendicke • E. Walter
Cost-Effectiveness of AI-Assisted Detection of Apical Periodontitis on Panoramic Radiographs.
International Endodontic Journal. Mar. 2026. DOI

[635]

C. Naumzik • A. Maarouf • S. Feuerriegel • M. Weinmann
Beyond Means: A Dynamic Framework for Predicting Customer Satisfaction.
International Journal of Research in Marketing In press. Mar. 2026. DOI

[634]

R. Hornung • A. Hapfelmeier
Automating airborne pollen classification: Identifying and interpreting hard samples for classifiers.
Journal of Classification. Mar. 2026. DOI

[633]

A. S. Meidert • R. Hornung • A. Laska • J. Esser • F. Brandes • S. Berthold • M. Borrmann • V. Huge
Effect of ice-lollies on the recovery time after anaesthesia: protocol for a cluster-randomised trial (Icesthesia).
Perioperative Medicine 15.32. Mar. 2026. DOI

[632]

H. Lia • T. Nagler • C. Czado
Modeling cold-related excess deaths via stationary vine copulas.
Scandinavian Actuarial Journal. Mar. 2026. DOI

[631]

M. Becker • L. Schneider • M. Binder • L. Kotthoff • B. Bischl
mlr3mbo: Bayesian Optimization in R.
Preprint (Mar. 2026). arXiv GitHub

[630]

E. F. Bülbül • S. Bang • K. George • G. Bianchi • P. Raj • S. Chung • V. Pauline • R. Hochstrasser • H. A. Minas • W. A. M. Elgaher • A. M. Kany • A. K. H. Hirsch • S. Schmitt • D. W. Heinz • O. V. Kalinina • D. Klakow • K. A. J. Bozhüyük
Generative AI designs functional thiolation domains for reprogramming non-ribosomal peptide synthetases.
Preprint (Mar. 2026). DOI

[629]

V. Bürger • M. Besouw • J. Fehr • R. Minocher • E. Moorhead • I. Velarde • L. Agha-Mir-Salim • J. Amann • A. Bannach-Brown • D. B. Blumenthal • K. Hair • B. Heinrichs • M. Herrmann • E. Hofvenschiöld • S. Holm • A. A. H. de Hond • S. Kijewski • S. McLennan • T. Minssen • M. S. Nobile • N. Pfeifer • J. L. Rohmann • T. Ross-Hellauer • M. Slavkovik • K. Tafur • E. Viganò • M. Westerlund • T. Weissgerber • V. I. Madai
How Meta-research Can Pave the Road Towards Trustworthy AI In Healthcare: Catalogue of Ideas and Roadmap for Future Research.
Preprint (Mar. 2026). arXiv

[628]

L. Burk • F. K. Ewald • G. Casalicchio • M. N. Wright • B. Bischl
xplainfi: Feature Importance and Statistical Inference for Machine Learning in R.
Preprint (Mar. 2026). arXiv

[627]

F. Ewald • M. Binder • M. Feurer • B. Bischl • G. Casalicchio
CASHomon Sets: Efficient Rashomon Sets Across Multiple Model Classes and their Hyperparameters.
Preprint (Mar. 2026). arXiv

[626]

S. Firmani • F. Steinbauer • G. Kasneci • A. Marsico • M. Horlacher
RIBEX: Predicting and Explaining RNA Binding Across Structured and Intrinsically Disordered Regions (IDR)-rich Proteins.
Preprint (Mar. 2026). DOI

[625]

E. Garces Arias • N. Sapargali • C. Heumann • M. Aßenmacher
The Truncation Blind Spot: How Decoding Strategies Systematically Exclude Human-Like Token Choices.
Preprint (Mar. 2026). arXiv

[624]

E. Javurek • D. Frauen • Y. Wang • S. Feuerriegel
Generalized Bayes for Causal Inference.
Preprint (Mar. 2026). arXiv

[623]

L. Mareis • M. Drton
Cost-Aware Optimized Front-Door Experimental Design.
Preprint (Mar. 2026). arXiv

[622]

F. A. Razakason • D. Racek • P. W. Thurner • G. Kauermann
Assessing Reporting Delays in ACLED Conflict Event Data.
Preprint (Mar. 2026). arXiv

[621]

B. Riegler • J. Odgers • V. Fortuin
Standard Acquisition Is Sufficient for Asynchronous Bayesian Optimization.
Preprint (Mar. 2026). arXiv

[620]

M. Rave • G. Kauermann
Deriving Duration Time From Occupancy Data—A Case Study in the Length of Stay in Intensive Care Units for COVID-19 Patients.
Biometrical Journal 68.1. Feb. 2026. DOI

[619]

D. S. Bové • H. Seibold • A.-L. Boulesteix • J. Manitz • A. Gasparini • B. K. Günhan • O. Boix • A. Schüler • S. Fillinger • S. Nahnsen • A. E. Jacob • T. Jaki
The statistical software revolution in pharmaceutical development: challenges and opportunities in open source.
Drug Discovery Today. Feb. 2026. DOI

[618]

R. Schwank • M. Drton
On the distance between mean and geometric median in high dimensions.
Statistics and Probability Letters Early Access.110679. Feb. 2026. DOI

[617]

T. Brock • T. Nagler
Fast Rates for Nonstationary Weighted Risk Minimization.
Preprint (Feb. 2026). arXiv

[616]

R. Hornung • L. Németh • O. Zadorozhny • T. Ullmann • M. Kammer • R. Killick • C. J. Paciorek • J. Chiquet • M. Herrmann • L. Batinovíc • R. Carlsson • P. Neuvial • B. Hejblum • J. Wrobel • A.-L. Boulesteix • K. Tabelow
Overcoming Barriers to Computational Reproducibility.
Preprint (Feb. 2026). arXiv

[615]

S. H. Langbein • H. Baniecki • F. Fumagalli • N. Koenen • M. N. Wright • J. Herbinger
Functional Decomposition and Shapley Interactions for Interpreting Survival Models.
Preprint (Feb. 2026). arXiv

[614]

J. Persson • J. Bakker • D. Bohle • S. Feuerriegel • F. Wangenheim
Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects.
Preprint (Feb. 2026). arXiv

[613]

M. Schröder • M. Oprescu • S. Feuerriegel • N. Kallus
Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework.
Preprint (Feb. 2026). arXiv

[612]

Y. Wang • D. Frauen • E. Javurek • K. Hess • Y. Ma • S. Feuerriegel
Targeted Synthetic Control Method.
Preprint (Feb. 2026). arXiv

[611]

H. M. Wong • P. Heesen • P. Janetzky • M. Bendszus • S. Feuerriegel
MedClarify: An information-seeking AI agent for medical diagnosis with case-specific follow-up questions.
Preprint (Feb. 2026). arXiv

[610]

Q. Xu • D. Rügamer • H. Wenz • J. Fontana • N. Meggyeshazi • A. Bender • M. E. Maros
Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis.
Preprint (Feb. 2026). arXiv

[609]

M. Wever • M. Muschalik • F. Fumagalli • M. Lindauer
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[608]

Q. Xu • D. Rügamer • A. Bender • M. E. Maros
Deep generative models in digital subtraction angiography (DSA) and X-ray angiography: a systematic review.
Artificial Intelligence Review 59.2. Jan. 2026. DOI

[607]

C. Chemery • H. Edelhoff • L. Bothmann
Beyond Off-the-Shelf Models: A Lightweight and Accessible Machine Learning Pipeline for Ecologists Working with Image Data.
Preprint (Jan. 2026). arXiv

[606]

J. Herbinger • G. Laberge • M. Muschalik • Y. Pequignot • M. N. Wright • F. Fumagalli
GRANITE: A Generalized Regional Framework for Identifying Agreement in Feature-Based Explanations.
Preprint (Jan. 2026). arXiv

[605]

R. Hornung • A. Hapfelmeier
Unity Forests: Improving Interaction Modelling and Interpretability in Random Forests.
Preprint (Jan. 2026). arXiv

[604]

A. Maarouf • A. Bakiaj • S. Feuerriegel
Predicting Startup Success Using Large Language Models: A Novel In-Context Learning Approach.
Preprint (Jan. 2026). arXiv

[603]

B. S. Siepe • F. Bartoš • A.-L. Boulesteix • D. W. Heck • A. Peikert • A. Sarafoglou • S. Pawel
Why, when, and how to (or not to)preregister a simulation study.
Preprint (Jan. 2026). DOI

[602]

N. Sturma • M. Kranzlmueller • I. Portakal • M. Drton
Matching Criterion for Identifiability in Sparse Factor Analysis.
Preprint (Jan. 2026). arXiv

[601]

C. Yuan • B. Ma • Z. Zhang • B. Prenkaj • F. Kreuter • G. Kasneci
Moral Lenses, Political Coordinates: Towards Ideological Positioning of Morally Conditioned LLMs.
Preprint (Jan. 2026). arXiv

[600]

S. Urchs • V. Thurner • M. Aßenmacher • C. Heumann • S. Thiemichen
Fair Play in the Newsroom: Actor-Based Filtering Gender Discrimination in Text Corpora.
Eval4NLP @AACL 2025 - 5th Workshop on Evaluation and Comparison of NLP Systems at the 4th Asia-Pacific Chapter of the Association for Computational Linguistics. Mumbai, India, Dec 20-24, 2025. URL

[599]

C. Sauer
Optimistic bias in the evaluation of statistical methods: illustrations and possible solutions.
Dissertation LMU München. Dec. 2025. DOI

[598]

L. Wimmer
Representing and quantifying predictive uncertainty in machine learning.
Dissertation LMU München. Dec. 2025. DOI

[597]

I. Ziegler • B. Ma • B. Bischl • B. Schubert • E. Dorigatti
Enhancing Multi-Epitope Vaccine Effectiveness Through State-of-the-Art Proteasomal Cleavage Prediction With Deep Learning.
BIPM 2025 - IEEE International Conference on Bioinformatics and Biomedicine. Wuhan, China, Dec 15-18, 2025. DOI GitHub

[596]

J. Kobialka • E. Sommer • J. Kwon • D. Dold • D. Rügamer
On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors.
EIML @EurIPS 2025 - Workshop on Epistemic Intelligence in Machine Learning at the European Conference on Information Processing Systems. Copenhagen, Denmark, Dec 03-05, 2025. URL

[595]

R. D. Paul • J. Seiffarth • D. Rügamer • H. Scharr • K. Nöh
Reliable Cell Trackers Say 'I dunno!'.
MedEurIPS @EurIPS 2025 - Workshop Medical Imaging meets EurIPS at the European Conference on Information Processing Systems. Copenhagen, Denmark, Dec 03-05, 2025. URL

[594]

S. Dandl • F. K. Ewald • E. Valero-Leal • B. Bischl • K. Blesch
Technical Considerations for XAI in AI Governance.
PAIG @EurIPS 2025 - Workshop on Private AI Governance at the European Conference on Information Processing Systems. Copenhagen, Denmark, Dec 03-05, 2025. URL

[593]

M. Abrahamowicz • M.-E. Beauchamp • A.-L. Boulesteix • T. P. Morris • W. Sauerbrei • J. S. Kaufman • o. b. o. t. STRATOS Simulation Panel
Efficient Computation of Image Persistence.
Discrete and Computational Geometry 74.4. Dec. 2025. DOI

[592]

S. Dandl • B. Bischl • L. Bothmann
Interpretable Machine Learning for Official Statistics.
Foundations and Advances of Machine Learning in Official Statistics. Dec. 2025. DOI

[591]

H. Schulz-Kümpel • A.-L. Boulesteix • S. F. Fischer • R. Hornung
Challenges in Resampling-Based Performance Estimation.
Foundations and Advances of Machine Learning in Official Statistics. Dec. 2025. DOI

[590]

S. Dandl • A. Hofheinz • M. Binder • B. Bischl • G. Casalicchio
counterfactuals: An R Package for Counterfactual Explanation Methods.
Journal of Statistical Software 115.9. Dec. 2025. DOI

[589]

F. Sergeev • M. Burger • P. Leshetkina • V. Fortuin • G. Rätsch • R. Kuznetsova
Data-Driven Discovery of Feature Groups in Clinical Time Series.
ML4H 2025 - Machine Learning for Health Symposium. San Diego, CA, USA, Dec 01-02, 2025. URL

[588]

T. Nagler
Simplified vine copula models: State of science and affairs.
Risk Sciences 1.100022. Dec. 2025. DOI

[587]

K. Dorman • K. Breitenwieser • L. Fischer • D. Zhang • V. Probst • L. Weiss • K. Heinrich • W. G. Kunz • J. W. Holch • C. Gießen-Jung • M. Haas • S. Boeck • M. von Bergwelt-Baildon • T. Landfarth • R. Hornung • J. Casuscelli • K. Berger-Thürmel • V. Heinemann • C. B. Westphalen • A.
Real-world analysis of immune checkpoint inhibitor efficacy and response predictors in patients treated at the CCCMunichLMU outpatient clinic.
Scientific Reports 15.43269. Dec. 2025. DOI

[586]

L. Hölbling • S. Maier • S. Feuerriegel
A Meta-Analysis of the Persuasive Power of Large Language Models.
Scientific Reports. Dec. 2025. Early Access. DOI

[585]

A. Alvandi • M. Rezaei
Revisiting Theory of Contrastive Learning for Domain Generalization.
Preprint (Dec. 2025). arXiv

[584]

E. Özeren • M. Aßenmacher
Reinforcement Learning for Latent-Space Thinking in LLMs.
Preprint (Dec. 2025). arXiv

[583]

V. Pauline • T. Höppe • K. Neklyudov • A. Tong • S. Bauer • A. Dittadi
Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction.
Preprint (Dec. 2025). arXiv

[582]

I. Tretow • M. Schwebel • S. Feuerriegel • T. Treffers • I. M. Welpe
The Effect of LLM Assistance on Diagnostic Accuracy: A Meta-Analysis.
Preprint (Dec. 2025). DOI

[581]

Y. Wang • D. Frauen • J. Schweisthal • M. Schröder • S. Feuerriegel
How reliable are treatment effects in clinical trials with dropout?
CauScien @NeurIPS 2025 - Workshop on Uncovering Causality in Science at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[580]

H. Amad • Z. Qian • D. Frauen • J. Piskorz • S. Feuerriegel • M. van der Schaar
Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[579]

D. Frauen • V. Melnychuk • J. Schweisthal • M. van der Schaar • S. Feuerriegel
Treatment Effect Estimation for Optimal Decision-Making.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[578]

D. Frauen • M. Schröder • K. Heß • S. Feuerriegel
Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[577]

M. Kmicikiewicz • V. Fortuin • E. Szczurek
ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[576]

Y. Ma • D. Frauen • J. Schweisthal • S. Feuerriegel
LLM-Driven Treatment Effect Estimation Under Inference Time Text Confounding.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[575]

B. M. G. Nielsen • E. Marconato • A. Dittadi • L. Gresele
When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[574]

Y. Ozyurt • T. Almaci • S. Feuerriegel • M. Sachan
Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[573]

M. Schröder • D. Frauen • J. Schweisthal • K. Heß • V. Melnychuk • S. Feuerriegel
Conformal Prediction for Causal Effects of Continuous Treatments.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[572]

A. Crăciun • D. Ghoshdastidar
Non-Singularity of the Gradient Descent Map for Neural Networks with Piecewise Analytic Activations.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Spotlight Presentation. URL

[571]

C. Kolb • L. Frost • B. Bischl • D. Rügamer
Differentiable Sparsity via D-Gating: Simple and Versatile Structured Penalization.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Spotlight Presentation. URL

[570]

E. Panagiotou • B. Ronval • A. Roy • L. Bothmann • B. Bischl • S. Nijssen • E. Ntoutsi
TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees.
ICDM 2025 - 25th IEEE International Conference on Data Mining. Washington DC, USA, Nov 12-15, 2025. DOI

[569]

E. Garces Arias • H. Blocher • J. Rodemann • M. Aßenmacher • C. Jansen
Statistical Multicriteria Evaluation of LLM-Generated Text.
INLG 2025 - 18th International Natural Language Generation Conference. Hanoi, Vietnam, Nov 05-09, 2025. URL

[568]

M. Amin • M. Aßenmacher
Do Companies Reveal Their Own Fraud? - A Novel Data Set for Fraud Detection Based on 10-K Reports.
FinNLP @EMNLP 2025 - 10th Workshop on Financial Technology and Natural Language Processing at the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[567]

Y. Ding • E. Garces Arias • M. Li • J. Rodemann • M. Aßenmacher • D. Chen • G. Fan • C. Heumann • C. Zhang
GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation.
Findings @EMNLP 2025 - Findings of the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub

[566]

M. Sengupta • M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier • D. Ghosh • H. Wachsmut
Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions.
Findings @EMNLP 2025 - Findings of the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[565]

C. Gruber • H. Alber • B. Bischl • G. Kauermann • B. Plank • M. Aßenmacher
Revisiting Active Learning under (Human) Label Variation.
NLPerspectives @EMNLP 2025 - 4th Workshop on Perspectivist Approaches to NLP at the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[564]

E. Garces Arias • J. Rodemann • C. Heumann
The Geometry of Creative Variability: How Credal Sets Expose Calibration Gaps in Language Models.
UncertaiNLP @EMNLP 2025 - 2nd Workshop on Uncertainty-Aware NLP at the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub

[563]

V. Lehmann • M. Hilpert • Z. Mostaani • S. Hovsepyan • E. Wallace • C. Verzat • S. Feuerriegel • M. Kraus • J. Rosenthal • G. Yilmaz • M. M. Doss • C. Stettler
Listening to Hypoglycemia: Voice as a Biomarker for Detection of a Medical Emergency Using Machine Learning.
Diabetes Care 49.1. Nov. 2025. DOI

[562]

N. Krueger • S. Schallmoser • R. Desai • S. Wang • H. Schunkert • T. Dreischulte • Schneeweiss • A. Kastrati • S. Feuerriegel
Predicting individualized treatment effects of prasugrel vs ticagrelor for acute coronary syndrome: a post hoc analysis of a randomized clinical trial.
European Heart Journal 46.Supplement 1. Nov. 2025. URL

[561]

K. Flöge • S. Udayakumar • J. Sommer • M. Piraud • S. Kesselheim • V. Fortuin • S. Günneman • K. J. van der Weg • H. Gohlke • E. Merdivan • A. Bazarova
OneProt: Towards multi-modal protein foundation models via latent space alignment of sequence, structure, binding sites and text encoders.
PLOS Computational Biology 21.11. Nov. 2025. DOI

[560]

J. Topalis • J. Dexl • K. Jeblick • R. Klaar • C. Kurz • T. Löhr • A. Mittermeier • B. Schachtner • A. T. Stüber • T. Weber • P. Wesp • J. Ricke • M. Seidensticker • G. Landry • M. Ingrisch • O. Dietrich
Fast machine learning image reconstruction of radially undersampled k-space data for low-latency real-time MRI.
PLOS One 20.11. Nov. 2025. DOI

[559]

N. Bouchahda • F. Scheipl • W. Rouetbi • K. Hafi • M. Y. Kallela • A. Najjar • N. B. Mahmoud • M. B. Salem • M. H. Ibrahim • S. Habib • H. Mani • S. Aloui • M. B. Messaoud • H. Skhiri
Left ventricular untwist determines intradialytic hemodynamics and outcomes in mildly reduced and preserved ejection fraction patients.
Physiological Reports 13.21. Nov. 2025. DOI

[558]

M. Herrmann • M. Herrmann
Discussion of the Paper 'Connecting Model-Based and Model-Free Approaches to Linear Least Squares Regression' by Lutz Dümbgen and Laurie Davies (2024).
Statistica 84. Nov. 2025. DOI GitHub

[557]

S. Lumpp • M. Drton
On weak convergence of Gaussian conditional distributions.
Statistics and Probability Letters 226.110497. Nov. 2025. DOI

[556]

F. J. D. Lange • J. C. Wilcke • S. Hoffmann • M. Herrmann • A.-L. Boulesteix
On 'confirmatory' methodological research in statistics and related fields.
Statistics in Medicine 44.25-27. Nov. 2025. DOI

[555]

S. F. Fischer • J. Zobolas • R. Sonabend • M. Becker • M. Lang • M. Binder • L. Schneider • L. Burk • P. Schratz • B. C. Jaeger • S. A. Lauer • L. A. Kapsner • M. Mücke • Z. Wang • D. Pulatov • K. Ganz • H. Funk • L. Harutyunyan • P. Camilleri • P. Kopper • A. Bender • B. Zhou • N. German • L. Koers • A. Nazarova • B. Bischl
mlr3extralearners: Expanding the mlr3 Ecosystem with Community-Driven Learner Integration.
The Journal of Open Source Software 10.115. Nov. 2025. DOI

[554]

S. Feuerriegel • A. Maarouf • S. Demir • M. Weinmann
Analyzing heterogeneity in the effects of behavioral climate interventions on individual beliefs across sociodemographics, attitudes, and norms.
Preprint (Nov. 2025). DOI

[553]

J. Gauss • T. Nagler
Properties of stepwise parameter estimation in high-dimensional vine copulas.
Preprint (Nov. 2025). arXiv

[552]

V. Gkolemis • C. Diou • D. Kyriakopoulos • K. Tsopelas • J. Herbinger • H. Baniecki • D. Rontogiannis • L. Kavouras • M. Muschalik • T. Dalamagas • E. Ntoutsi • B. Bischl • G. Casalicchio
Effector: A Python package for regional explanations.
Preprint (Nov. 2025). arXiv GitHub

[551]

R. Kassoumeh • D. Rügamer • H. Oppel
Enhancing Heavy Rain Nowcasting with Multimodal Data: Integrating Radar and Satellite Observations.
Preprint (Nov. 2025). arXiv GitHub

[550]

P. C. Münch • N. Safaei • R. Mreches • M. Binder • Y. Han • G. Robertson • E. A. Franzosa • C. Huttenhower • A. C. McHardy
Comparative Assessment of Large Language Models for Microbial Phenotype Annotatione.
Preprint (Nov. 2025). DOI

[549]

R. D. Paul • J. Seiffarth • D. Rügamer • K. Nöh • H. Scharr
How To Make Your Cell Tracker Say 'I dunno!'.
ICCV 2025 - IEEE/CVF International Conference on Computer Vision. Honolulu, Hawai’i, Oct 19-23, 2025. DOI

[548]

Z. Jonassen • K. Lawrence • B. M. Wiesenfeld • S. Feuerriegel • D. Mann
A qualitative analysis of remote patient monitoring: how a paradox mindset can support balancing emotional tensions in the design of healthcare technologies.
CSCW 2025 - 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. Bergen, Norway, Oct 18-22, 2025. DOI

[547]

Y. S. Wang • M. Kolar • M. Drton
Confidence Sets for Causal Orderings.
Journal of the American Statistical Association. Oct. 2025. DOI

[546]

L. Skapetze • D. Koller • A. Zwergal • S. Feuerriegel • A. Rubinski • E. Grill
Monitoring changes in vitamin D levels during the COVID-19 pandemic with routinely-collected laboratory data.
Nature Communications 16.8772. Oct. 2025. DOI

[545]

K. Hechinger • C. Schweden • X. Zhu • G. Kauermann
Human-in-the-loop: Towards label embeddings for assessing classification difficulty.
Statistical Modelling Early Access. Oct. 2025. DOI

[544]

D. Dobler • H. Binder • A.-L. Boulesteix • J.-B. Igelmann • D. Köhler • U. Mansmann • M. Pauly • A. Scherag • M. Schmid • A. A. Tawil • S. Weber
ChatGPT as a Tool for Biostatisticians: A Tutorial on Applications, Opportunities, and Limitations.
Statistics in Medicine 44.23-24. Oct. 2025. DOI

[543]

M. Wünsch • M. Noltenius • M. Mohr • T. P. Morris • A.-L. Boulesteix
Rethinking the Handling of Method Failure in Comparison Studies.
Statistics in Medicine 44.23-24. Oct. 2025. DOI

[542]

N. Lercari • A. Fandrei • Z. Zellmann • Y. Du • M. Yacoub • D. Calderone • R. Brancato • S. Scerra • D. Tanasi • R. Lanteri • D. Rügamer
Semi-automated LiDAR Vegetation Classification for Mediterranean Archaeology: Designing a Pipeline Leveraging a Multi-Layer Stacked Ensemble Approach.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-M-9-2025. Oct. 2025. DOI GitHub

[541]

S. Rittel • S. Tschiatschek
Expressiveness of Parametrized Distributions over DAGs for Causal Discovery.
Transactions on Machine Learning Research. Oct. 2025. URL

[540]

D. Köhler • D. Rügamer • L. Boyle • K. Maloney • M. Schmid
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects.
npj Artificial Intelligence 1.34. Oct. 2025. DOI

[539]

A.-L. Boulesteix • P. Callahan • L. Hanssum • V. Gaertner • E. Hoster
Bridging the Gap Between Methodological Research and Statistical Practice: Toward Translational Simulation Research.
Preprint (Oct. 2025). arXiv

[538]

A. Khot • M. Oprescu • M. Schröder • A. Kagawa • X. Luo
Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference.
Preprint (Oct. 2025). arXiv

[537]

M. Kosmas • A.-S. Mayer • S. Feuerriegel • F. Bodendorf
From Code to Culture: Aligning Large Language Models with Corporate Values.
Preprint (Oct. 2025). DOI

[536]

A. Maarouf • K. T. Greene • J. N. Shapiro • S. Feuerriegel • M. H. Ribeiro
Short-Form Video Platforms Drive Mobile Usage.
Preprint (Oct. 2025). DOI

[535]

T. Vatter • T. Nagler
Throwing Vines at the Wall: Structure Learning via Random Search.
Preprint (Oct. 2025). arXiv

[534]

Y. Wang • D. Frauen • J. Schweisthal • M. Schröder • S. Feuerriegel
Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring.
Preprint (Oct. 2025). arXiv

[533]

P. Kopper • D. Rügamer • R. Sonabend • B. Bischl • A. Bender
On Training Survival Models with Scoring Rules.
ECML-PKDD 2025 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI

[532]

E. Özeren • A. Ulbrich • S. Filimon • D. Rügamer • A. Bender
Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety.
ECML-PKDD 2025 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI

[531]

J. Rodemann • F. Croppi • P. Arens • Y. Sale • J. Herbinger • B. Bischl • E. Hüllermeier • T. Augustin • C. J. Walsh • G. Casalicchio
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration For Exosuit Personalization.
ECML-PKDD 2025 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI GitHub

[530]

J. Herbinger • M. N. Wright • T. Nagler • B. Bischl • G. Casalicchio
Decomposing Global Feature Effects Based on Feature Interactions.
ECML-PKDD 2025 - Nectar Track at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. URL

[529]

S. Rittel • S. Tschiatschek
Distributions over DAGs for Causal Discovery: Limitations of Expressiveness.
MLG @ECML-PKDD 2025 - 22nd International Workshop on Mining and Learning with Graphs at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. PDF

[528]

F. K. Ewald • L. Bothmann • M. N. Wright • B. Bischl • G. Casalicchio • G. König
A Guide to Feature Importance Methods for Scientific Inference.
Nectar Track @ECML-PKDD 2025 - Nectar Track at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI

[527]

T. Zehle • M. Schlager • T. Heiß • M. Feurer
CAPO: Cost-Aware Prompt Optimization.
Methods Track @AutoML 2025 - Methods Track at the International Conference on Automated Machine Learning. New York City, NY, USA, Sep 08-11, 2025. URL

[526]

L. Schneider • B. Bischl • M. Feurer
Overtuning in Hyperparameter Optimization.
Methods Track @AutoML 2025 - Methods Track at the International Conference on Automated Machine Learning. New York City, NY, USA, Sep 08-11, 2025. Best Paper Award. URL

[525]

A. S. Gutmann • M. M. Mandl • C. Rieder • D. J. Hoechter • K. Dietz • B. P. Geisler • A.-L. Boulesteix • R. Tomasi • L. C. Hinske
Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy.
BMC Medical Informatics and Decision Making 25.326. Sep. 2025. DOI

[524]

P. Esser • M. Fleissner • D. Ghoshdastidar
Theoretical Foundations of Representation Learning using Unlabeled Data: Statistics and Optimization.
Preprint (Sep. 2025). arXiv

[523]

L. Hölbling • S. Maier • S. Feuerriegel
The Persuasive Power of LLMs: A Systematic Literature Review and Meta-Analysis.
Preprint (Sep. 2025). DOI

[522]

J. Persson • S. Feuerriegel • C. Kadar
Learning from Editorial Decisions: Optimizing Audience-Wide Content Promotions with Causal Machine Learning.
Preprint (Sep. 2025). DOI

[521]

H. Tenzer • O. Abidi • S. Feuerriegel
Designing LLMs for cultural sensitivity: Evidence from English-Japanese translation.
Preprint (Sep. 2025). arXiv

[520]

S. Wiegrebe • J. Piller • M. Gorski • M. Behr • H. Küchenhoff • I. M. Heid • A. Bender
Multi-state Models For Modeling Disease Histories Based On Longitudinal Data.
Preprint (Sep. 2025). arXiv

[519]

J. Zobolas • A.-M. George • A. López • S. F. Fischer • M. Becker • T. Aittokallio
Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data.
Preprint (Sep. 2025). arXiv

[518]

Y. Ma • J. Schweisthal • H. Zhang • S. Feuerriegel
A Diffusion-Based Method for Learning the Multi-Outcome Distribution of Medical Treatments.
KDD 2025 - 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Toronto, ON, Canada, Aug 03-07, 2025. DOI

[517]

D. Strieder • M. Drton
Identifying total causal effects in linear models under partial homoscedasticity.
International Journal of Approximate Reasoning 183.109455. Aug. 2025. DOI

[516]

H. Funk • R. Ludwig • H. Küchenhoff • T. Nagler
Towards more realistic climate model outputs: A multivariate bias correction based on zero-inflated vine copulas.
Journal of the Royal Statistical Society. Series C (Applied Statistics).qlaf044. Aug. 2025. DOI

[515]

S. Urchs • V. Thurner • M. Aßenmacher • L. Bothmann • C. Heumann • S. Thiemichen
Are All Genders Equal in the Eyes of Algorithms? -- Analysing Search and Retrieval Algorithms for Algorithmic Gender Fairness.
Preprint (Aug. 2025). arXiv

[514]

M. Mandl
Addressing researcher degrees of freedom in applications, methodological research, and teaching.
Dissertation LMU München. Jul. 2025. DOI

[513]

D. Bär
Computational approaches to enhance the integrity of social media: from detection to intervention.
Dissertation LMU München. Jul. 2025. DOI

[512]

B. Ma • B. Yoztyurk • A.-C. Haensch • X. Wang • M. Herklotz • F. Kreuter • B. Plank • M. Aßenmacher
Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study.
ACL 2025 - 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI

[511]

S. Urchs • V. Thurner • M. Aßenmacher • C. Heumann • S. Thiemichen
taz2024full: Analysing German Newspapers for Gender Bias and Discrimination across Decades.
Findings @ACL 2025 - Findings at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI

[510]

E. Garces Arias • H. Blocher • J. Rodemann • M. Li • C. Heumann • M. Aßenmacher
Towards Better Open-Ended Text Generation: A Multicriteria Evaluation Framework.
GEM2 @ACL 2025 - 4th Workshop on Generation, Evaluation and Metrics at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. URL

[509]

A. Stephan • D. Zhu • M. Aßenmacher • X. Shen • B. Roth
From Calculation to Adjudication: Examining LLM Judges on Mathematical Reasoning Tasks.
GEM2 @ACL 2025 - 4th Workshop on Generation, Evaluation and Metrics at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. URL

[508]

S. F. Fischer • B. Bischl
Constructing Confidence Intervals for ’the’ Generalization Error.
Statistical Computing 2025 - 55. Arbeitstagung der Arbeitsgruppen Statistical Computing, Klassifikation und Datenanalyse in den Biowissenschaften. Ulm, Germany, Jul 27-30, 2025. PDF

[507]

M. Koshil • M. Feurer • K. Eggensperger
In-Context Learning of Soft Nearest Neighbor Classifiers for Intelligible Tabular Machine Learning.
TRL @ACL 2025 - 4th Table Representation Learning Workshop at the 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI

[506]

M. Arpogaus • T. Kneib • T. Nagler • D. Rügamer
Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals.
UAI 2025 - 41st Conference on Uncertainty in Artificial Intelligence. Rio de Janeiro, Brazil, Jul 21-25, 2025. URL

[505]

M. Drton • M. Garrote-López • N. Nikov • E. Robeva • Y. S. Wang
Causal Discovery for Linear Non-Gaussian Models with Disjoint Cycles.
UAI 2025 - 41st Conference on Uncertainty in Artificial Intelligence. Rio de Janeiro, Brazil, Jul 21-25, 2025. URL GitHub

[504]

S. Müller • A. Reuter • N. Hollmann • D. Rügamer • F. Hutter
Position: The Future of Bayesian Prediction Is Prior-Fitted.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[503]

T. Pielok • B. Bischl • D. Rügamer
Revisiting Unbiased Implicit Variational Inference.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[502]

A. Reuter • T. G. J. Rudner • V. Fortuin • D. Rügamer
Can Transformers Learn Full Bayesian Inference in Context?
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[501]

R. Schulte • D. Rügamer • T. Nagler
Adjustment for Confounding using Pre-Trained Representations.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[500]

J. Schweisthal • D. Frauen • M. Schröder • K. Heß • N. Kilbertus • S. Feuerriegel
Learning Representations of Instruments for Partial Identification of Treatment Effects.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[499]

D. Tramontano • Y. Kivva • S. Salehkaleybar • N. Kiyavash • M. Drton
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[498]

A. Uselis • A. Dittadi • S. J. Oh
Does Data Scaling Lead to Visual Compositional Generalization?
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL GitHub

[497]

V. M. Singh • A. G. V. Asiares • L. S. Schuhmacher • K. Rendall • S. Weißbrod • D. Rügamer • I. Körte
An Interpretable Representation Learning Approach for Diffusion Tensor Imaging.
MIDL 2025 - Medical Imaging with Deep Learning. Salt Lake City, UT, USA, Jul 09-11, 2025. URL

[496]

R. Debelak • T. K. Koch • M. Aßenmacher • C. Stachl
From Embeddings to Explainability: A Tutorial on Large-Language-Model-Based Text Analysis for Behavioral Scientists.
Advances in Methods and Practices in Psychological Science 8.3. Jul. 2025. DOI

[495]

L. Hafner • G. Sturm • S. Lumpp • M. Drton • M. List
Single-cell differential expression analysis between conditions within nested settings.
Briefings in Bioinformatics 26.4. Jul. 2025. DOI

[494]

D. Geissler • A. Maarouf • D. Bär • N. Pröllochs • S. Feuerriegel
A comment on 'A 2 million-person, campaign-wide field experiment shows how digital advertising affects voter turnout'.
I4R Discussion Paper Series.237. Jul. 2025. URL

[493]

N. Palm • H. Palm
PROBLEM-TAILORED MULTI-OBJECTIVE OPTIMIZATION ALGORITHM CONSTRUCTION BY PARETO REFLECTIONS.
Journal of Mathematical Sciences. Jul. 2025. DOI

[492]

J. Weberpals • S. Feuerriegel • M. van der Schaar • K. L. Kehl
Opportunities for Causal Machine Learning in Precision Oncology.
NEJM AI 2.8. Jul. 2025. DOI

[491]

B. Bischl • G. Casalicchio • T. Das • M. Feurer • S. F. Fischer • P. Gijsbers • S. Mukherjee • A. C. Müller • L. Németh • L. Oala • L. Purucker • S. Ravi • J. N. van Rijn • P. Singh • J. Vanschoren • J. van der Velde • M. Wever
OpenML: Insights from 10 years and more than a thousand papers.
Patterns 6.7. Jul. 2025. DOI GitHub

[490]

M. M. Mandl • A.-L. Boulesteix • S. Burgess • V. Zuber
Outlier Detection in Mendelian Randomization.
Statistics in Medicine 44.15-17. Jul. 2025. DOI

[489]

E. Walter • T. Brock • P. Lahoud • N. Werner • F. Czaja • A. Tichy • C. Bumm • A. Bender • A. Castro • W. Teughels • F. Schwendicke • M. Folwaczny
Predictive modeling for step II therapy response in periodontitis - model development and validation.
npj Digital Medicine 8.445. Jul. 2025. DOI

[488]

N. Sturma • M. Drton
Trek-Based Parameter Identification for Linear Causal Models With Arbitrarily Structured Latent Variables.
Preprint (Jul. 2025). arXiv

[487]

L. Bothmann • P. A. Boustani • J. M. Alvarez • G. Casalicchio • B. Bischl • S. Dandl
Privilege Scores.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025. arXiv

[486]

L. Bothmann • K. Peters • B. Bischl
What is Fairness? On Protected Attributes and Fictitious Worlds.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025. URL

[485]

C. Leininger • S. Rittel • L. Bothmann
Overcoming Fairness Trade-offs via Pre-processing: A Causal Perspective.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025. URL

[484]

L. Waldmann • A. Shah • Y. Wang • N. Lehmann • A. J. Stewart • Z. Xiong • X. Zhu • S. Bauer • J. Chuang
Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation.
EARTHVISION @CVPR 2025 - Workshop EarthVision: Large Scale Computer Vision for Remote Sensing Imagery at the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. Best Paper Award. DOI

[483]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Preventing Sensitive Information Leakage via Post-hoc Orthogonalization with Application to Chest Radiograph Embeddings.
PAKDD 2025 - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Sydney, Australia, Jun 10-13, 2025. DOI GitHub

[482]

T. Boege • M. Drton • B. Hollering • S. Lumpp • P. Misra • D. Schkoda
Conditional independence in stationary distributions of diffusions.
Stochastic Processes and their Applications 184.104604. Jun. 2025. DOI

[481]

L. Gosch • M. Sabanayagam • D. Ghoshdastidar • S. Günnemann
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks.
Transactions on Machine Learning Research. Jun. 2025. URL

[480]

C. Benjamins • H. Graf • S. Segel • D. Deng • T. Ruhkopf • L. Hennig • S. Basu • N. Mallik • E. Bergman • D. Chen • F. Clément • A. Tornede • M. Feurer • K. Eggensperger • F. Hutter • C. Doerr • M. Lindauer
carps: A Framework for Comparing N Hyperparameter Optimizers on M Benchmarks.
Preprint (Jun. 2025). arXiv URL

[479]

T. Cheng • T. Vatter • T. Nagler • K. Chen
Vine Copulas as Differentiable Computational Graphs.
Preprint (Jun. 2025). arXiv

[478]

K. Göbler • T. Windisch • M. Drton
Nonlinear Causal Discovery for Grouped Data.
Preprint (Jun. 2025). arXiv

[477]

J. Min • H. Li • T. Nagler • S. Li
Assessing Climate-Driven Mortality Risk: A Stochastic Approach with Distributed Lag Non-Linear Models.
Preprint (Jun. 2025). arXiv

[476]

S. Schallmoser • J. Schweisthal • A. von Ehr • H. Ghanbari • F. Schiefenhövel • T. S. Valley • J. Wiens • S. Feuerriegel
Causal machine learning for assessing the effectiveness of off-label use of amiodarone in new-onset atrial fibrillation.
Preprint (Jun. 2025). DOI

[475]

M. Schöffel • E. Garces Arias • M. Wiedner • P. Ruppert • M. Li • C. Heumann • M. Aßenmacher
Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages.
Preprint (Jun. 2025). arXiv

[474]

L. Schneider
Advancing hyperparameter optimization: foundations, multiple objectives and algorithmic innovations informed through benchmarking.
Dissertation LMU München. May. 2025. DOI

[473]

D. Strieder
Structure Uncertainty in Causal Inference.
Dissertation TU München. May. 2025. URL

[472]

D. Dold • J. Kobialka • N. Palm • E. Sommer • D. Rügamer • O. Dürr
Paths and Ambient Spaces in Neural Loss Landscapes.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL

[471]

R. Schulte • D. Rügamer
Additive Model Boosting: New Insights and Path(ologie)s.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. Oral Presentation. URL

[470]

T. Nagler • T. Vatter
Solving Estimating Equations With Copulas.
Invited Talk @AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. Invited Talk. DOI

[469]

C. Kern • U. Fischer-Abaigar • J. Schweisthal • D. Frauen • R. Ghani • S. Feuerriegel • M. van der Schaar • F. Kreuter
Algorithms for reliable decision-making need causal reasoning.
Nature Computational Science 5. May. 2025. DOI

[468]

H. Löwe • C. A. Scholbeck • C. Heumann • B. Bischl • G. Casalicchio
fmeffects: An R Package for Forward Marginal Effects.
The R Journal 16.3. May. 2025. DOI

[467]

N. Holzner • S. Maier • S. Feuerriegel
Generative AI and Creativity: A Systematic Literature Review and Meta-Analysis.
Preprint (May. 2025). arXiv

[466]

J. Schröder • S. Howard • C. Eberle • J. Esslinger • N. Leopold-Kerschbaumer • K. V. Kepesidis • A. Döpp
Information-optimal measurement: From fixed sampling protocols to adaptive spectroscopy.
Preprint (May. 2025). arXiv

[465]

M. Schröder • J. Hartenstein • S. Feuerriegel
PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects.
Preprint (May. 2025). arXiv

[464]

R. Sonabend • J. Zobolas • R. Bin • P. Kopper • L. Burk • A. Bender
Examining marginal properness in the external validation of survival models with squared and logarithmic losses.
Preprint (May. 2025). arXiv

[463]

C. Zhang • S. Wu • Y. Chen • M. Aßenmacher • C. Heumann • Y. Men • G. Fan • J. Gama
OBD-Finder: Explainable Coarse-to-Fine Text-Centric Oracle Bone Duplicates Discovery.
Preprint (May. 2025). arXiv GitHub

[462]

T. Rochussen • V. Fortuin
Sparse Gaussian Neural Processes.
AABI 2025 - 7th Symposium on Advances in Approximate Bayesian Inference collocated with the 13th International Conference on Learning Representations. Singapore, Apr 29, 2025. URL

[461]

A. Wuttke • M. Aßenmacher • C. Klamm • M. M. Lang • Q. Würschinger • F. Kreuter
AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers.
LaTeCH-CLfL @NAACL 2025 - 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature at the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Albuquerque, NM, USA, Apr 29-May 04, 2025. DOI

[460]

M. Schöffel • M. Wiedner • E. Garces Arias • P. Ruppert • C. Heumann • M. Aßenmacher
Modern Models, Medieval Texts: A POS Tagging Study of Old Occitan.
NLP4DH 2025 - 5th International Conference on Natural Language Processing for Digital Humanities. Albuquerque, NM, USA, Apr 29-May 04, 2025. DOI

[459]

J. Kobialka • E. Sommer • J. Kwon • D. Dold • D. Rügamer
Approximate Posteriors in Neural Networks: A Sampling Perspective.
Workshop @AABI 2025 - Workshop at the 7th Symposium on Advances in Approximate Bayesian Inference collocated with the 13th International Conference on Learning Representations. Singapore, Apr 29, 2025. URL

[458]

T. Nagler • D. Rügamer
Uncertainty Quantification for Prior-Fitted Networks using Martingale Posteriors.
Workshop @AABI 2025 - Workshop at the 7th Symposium on Advances in Approximate Bayesian Inference collocated with the 13th International Conference on Learning Representations. Singapore, Apr 29, 2025. URL

[457]

D. Geißler • A. Maarouf • S. Feuerriegel
Analyzing User Characteristics of Hate Speech Spreaders on Social Media.
WWW 2025 - ACM Web Conference. Sydney, Australia, Apr 28-May 02, 2025. DOI

[456]

K. Forster • V. Wagner • L. Keil • M. A. Müller • T. Sellhorn • S. Feuerriegel
Tracking ESG Disclosures of European Companies with Retrieval-Augmented Generation.
Climate Change AI @ICLR 2025 - Workshop on Tackling Climate Change with Machine Learning at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[455]

T. Nagler • D. Rügamer
Uncertainty Quantification for Prior-Fitted Networks using Martingale Posteriors.
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. arXiv URL

[454]

A. Reuter • T. G. J. Rudner • V. Fortuin • D. Rügamer
Can Transformers Learn Full Bayesian Inference in Context?
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. arXiv URL

[453]

D. Rundel • E. Sommer • B. Bischl • D. Rügamer • M. Feurer
Efficiently Warmstarting MCMC for BNNs.
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[452]

J. Kobialka • E. Sommer • J. Kwon • D. Dold • D. Rügamer
Approximate Posteriors in Neural Networks: A Sampling Perspective.
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL

[451]

D. Frauen • K. Heß • S. Feuerriegel
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[450]

K. Heß • S. Feuerriegel
Stabilized Neural Prediction of Potential Outcomes in Continuous Time.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[449]

C. Kolb • T. Weber • B. Bischl • D. Rügamer
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[448]

Y. Li • D. Rügamer • B. Bischl • M. Rezaei
Calibrating LLMs with Information-Theoretic Evidential Deep Learning.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL GitHub

[447]

M. Schröder • V. Melnychuk • S. Feuerriegel
Differentially private learners for heterogeneous treatment effects.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[446]

E. Sommer • J. Robnik • G. Nozadze • U. Seljak • D. Rügamer
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[445]

Y. Wang • M. Schröder • D. Frauen • J. Schweisthal • K. Heß • S. Feuerriegel
Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[444]

H. Baniecki • G. Casalicchio • B. Bischl • P. Biecek
Efficient and Accurate Explanation Estimation with Distribution Compression.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL GitHub

[443]

L. Wimmer • B. Bischl • L. Bothmann
Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning.
SCSL @ICLR 2025 - Workshop on Spurious Correlation and Shortcut Learning: Foundations and Solutions at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[442]

C. Kolb • B. Bischl • D. Rügamer
Differentiable Attention Sparsity via Structured D-Gating.
SLLM @ICLR 2025 - Workshop on Sparsity in LLMs at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[441]

A. Reuter • T. G. J. Rudner • V. Fortuin • D. Rügamer
Can Transformers Learn Full Bayesian Inference in Context?
SynthData @ICLR 2025 - Workshop SynthData: Will Synthetic Data Finally Solve the Data Access Problem? at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[440]

L. Meynent • I. Melev • K. Schürholt • G. Kauermann • D. Borth
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction.
Weight Space Learning @ICLR 2025 - Workshop on Weight Space Learning at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. arXiv URL

[439]

H. A. Gündüz
Designing and optimizing deep learning methods for genomic sequencing data.
Dissertation LMU München. Apr. 2025. DOI

[438]

T. Weber
Advancing Deep Learning in medical imaging through generative modeling and representation learning.
Dissertation LMU München. Apr. 2025. DOI

[437]

M. Mironov • A. Marquard • D. Racek • C. Heumann • P. W. Thurner • M. Aßenmacher
A Geoparsing Pipeline for Multilingual Social Media Posts from Ukraine.
GeoExT @ECIR 2025 - 3rd International Workshop on Geographic Information Extraction from Texts at the 47th European Conference on Information Retrieval. Lucca, Italy, Apr 06-10, 2025. PDF

[436]

A. Maarouf • S. Feuerriegel • N. Pröllochs
A fused large language model for predicting startup success.
European Journal of Operational Research 322.1. Apr. 2025. DOI

[435]

A. Tejada-Lapuerta • P. Bertin • S. Bauer • H. Aliee • Y. Bengio • F. J. Theis
Causal machine learning for single-cell genomics.
Nature Genetics 57.4. Apr. 2025. DOI

[434]

N. Santhanam • H. E. Kim • D. Rügamer • A. Bender • S. Muthers • C. G. Cho • A. Alonso • K. Szabo • F.-S. Centner • H. Wenz • T. Ganslandt • M. Platten • C. Groden • M. Neumaier • F. Siegel • M. E. Maros
Machine learning-based forecasting of daily acute ischemic stroke admissions using weather data.
npj Digital Medicine 8.225. Apr. 2025. DOI

[433]

D. Martens • G. Shmueli • T. Evgeniou • K. Bauer • C. Janiesch • S. Feuerriegel • S. Gabel • S. Goethals • T. Greene • N. Klein • M. Kraus • N. Kühl • C. Perlich • W. Verbeke • A. Zharova • P. Zschech • F. Provost
Beware of 'Explanations' of AI.
Preprint (Apr. 2025). arXiv

[432]

C. Sauer • F. J. D. Lange • M. Thurow • I. Dormuth • A.-L. Boulesteix
Statistical parametric simulation studies based on real data.
Preprint (Apr. 2025). arXiv

[431]

L. Bothmann • S. Dandl • J. M. Alvarez • P. A. Boustani • B. Bischl
Privilege Scores for Fairness-Aware ML.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available. arXiv

[430]

L. Zumeta-Olaskoaga • A. Bender • D.-J. Lee
Flexible modelling of time-varying exposures in event history analysis.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available. DOI

[429]

L. Zumeta-Olaskoaga • A. Bender • D.-J. Lee
Flexible modelling of time-varying exposures and recurrent events to analyse training load effects in team sports injuries.
Journal of the Royal Statistical Society. Series C (Applied Statistics) 74.2. Mar. 2025. DOI

[428]

M. Schneble • G. Kauermann
Statistical modelling of on-street parking spot occupancy in smart cities.
Journal of the Royal Statistical Society. Series C (Applied Statistics) 74.4. Mar. 2025. DOI

[427]

D. Bär • N. Pröllochs • S. Feuerriegel
The role of social media ads for election outcomes: Evidence from the 2021 German election.
PNAS Nexus.pgaf073. Mar. 2025. DOI

[426]

R. Hornung • M. Nalenz • L. Schneider • A. Bender • L. Bothmann • F. Dumpert • B. Bischl • T. Augustin • A.-L. Boulesteix
Evaluating Machine Learning Models in Non-Standard Settings: An Overview and New Findings.
Statistical Science. Mar. 2025. To be published. Preprint available. arXiv URL

[425]

P. Bertin • J. D. Viviano • A. Tejada-Lapuerta • W. Wang • S. Bauer • F. J. Theis • Y. Bengio
A scalable gene network model of regulatory dynamics in single cells.
Preprint (Mar. 2025). arXiv

[424]

M. M. Mandl • F. Weber • T. Wöhrle • A.-L. Boulesteix
The impact of the storytelling fallacy on real data examples in methodological research.
Preprint (Mar. 2025). arXiv

[423]

R. Rehms • N. Ellenbach • V. Deffner • S. Hoffmann
Addressing complex structures of measurement error arising in the exposure assessment in occupational epidemiology using a Bayesian hierarchical approach.
Preprint (Mar. 2025). arXiv

[422]

H. Shi • M. Drton
On universal inference in Gaussian mixture models.
Preprint (Mar. 2025). arXiv

[421]

L. Burk • A. Bender • M. N. Wright
High-Dimensional Variable Selection With Competing Events Using Cooperative Penalized Regression.
Biometrical Journal 67.1. Feb. 2025. DOI

[420]

M. Wünsch • C. Sauer • M. Herrmann • L. C. Hinske • A.-L. Boulesteix
To tweak or not to tweak. How exploiting flexibilities in gene set analysis leads to over-optimism.
Biometrical Journal 67.1. Feb. 2025. DOI

[419]

D. Tschernutter • S. Feuerriegel
Data-driven dynamic police patrolling: An efficient Monte Carlo tree search.
European Journal of Operational Research 321.1. Feb. 2025. DOI

[418]

T. Willem • V. A. Shitov • M. D. Luecken • N. Kilbertus • S. Bauer • M. Piraud • A. Buyx • F. J. Theis
Biases in machine-learning models of human single-cell data.
Nature Cell Biology 27.2. Feb. 2025. DOI

[417]

S. Feuerriegel • A. Maarouf • D. Bär • D. Geißler • J. Schweisthal • N. Pröllochs • C. E. Robertson • S. Rathje • J. Hartmann • S. M. Mohammad • O. Netzer • A. A. Siegel • B. Plank • J. J. Van Bavel
Using natural language processing to analyse text data in behavioural science.
Nature Reviews Psychology 4. Feb. 2025. DOI

[416]

M. Drton • A. Grosdos • I. Portakal • N. Sturma
Algebraic Sparse Factor Analysis.
SIAM Journal on Applied Algebra and Geometry 9. Feb. 2025. DOI

[415]

E. Banzato • M. Drton • K. Saraf-Poor • H. Shi
Existence of Direct Density Ratio Estimators.
Preprint (Feb. 2025). arXiv

[414]

H. Bao • M. Schomaker
Addressing Positivity Violations in Continuous Interventions through Data-Adaptive Strategies.
Preprint (Feb. 2025). arXiv

[413]

H. Funk • R. Ludwig • H. Küchenhoff • T. Nagler
Modelling Climate Variables at High Temporal Resolution.
Preprint (Feb. 2025). DOI

[412]

J. Rodemann • E. Garces Arias • C. Luther • C. Jansen • T. Augustin
A Statistical Case Against Empirical Human-AI Alignment.
Preprint (Feb. 2025). arXiv

[411]

M. Surner • A. Khelil • L. Bothmann
Invariance Pair-Guided Learning: Enhancing Robustness in Neural Networks.
Preprint (Feb. 2025). arXiv

[410]

E. Garces Arias • M. Li • C. Heumann • M. Aßenmacher
Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation.
COLING 2025 - The 31st International Conference on Computational Linguistics. Abu Dhabi, United Arab Emirates, Jan 19-24, 2025. URL

[409]

M. Abrahamowicz • M.-E. Beauchamp • A.-L. Boulesteix • T. P. Morris • W. Sauerbrei • J. S. Kaufman • o. b. o. t. STRATOS Simulation Panel
Data-driven simulations to assess the impact of study imperfections in time-to-event analyses.
American Journal of Epidemiology 194.1. Jan. 2025. DOI

[408]

L. Bothmann • K. Peters
Fairness von KI – ein Brückenschlag zwischen Philosophie und Maschinellem Lernen.
Grenzen Künstlicher Intelligenz. Jan. 2025. DOI

[407]

H. Schulz-Kümpel • S. F. Fischer • T. Nagler • A.-L. Boulesteix • B. Bischl • R. Hornung
Constructing Confidence Intervals for 'the' Generalization Error – a Comprehensive Benchmark Study.
Journal of Data-centric Machine Learning Research 2.6. Jan. 2025. PDF

[406]

T. Weber • J. Dexl • D. Rügamer • M. Ingrisch
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition.
Radiology: Artificial Intelligence 7.2. Jan. 2025. DOI

[405]

R. Schwank • A. McCormack • M. Drton
Robust Score Matching.
Preprint (Jan. 2025). arXiv

[404]

Y. Zhang • Y. Li • X. Wang • Q. Shen • B. Plank • B. Bischl • M. Rezaei • K. Kawaguchi
FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models.
Compression Workshop @NeurIPS 2024 - Workshop on Machine Learning and Compression at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[403]

R. Dhahri • A. Immer • B. Charpentier • S. Günnemann • V. Fortuin
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihood.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[402]

Y. Ma • V. Melnychuk • J. Schweisthal • S. Feuerriegel
DiffPO: A causal diffusion model for learning distributions of potential outcomes.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[401]

V. Melnychuk • S. Feuerriegel • M. van der Schaar
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[400]

T. Nagler • L. Schneider • B. Bischl • M. Feurer
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[399]

D. Rügamer • B. X. W. Liew • Z. Altai • A. Stöcker
A Functional Extension of Semi-Structured Networks.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[398]

M. Koshil • T. Nagler • M. Feurer • K. Eggensperger
Towards Localization via Data Embedding for TabPFN.
TLR @NeurIPS 2024 - 3rd Table Representation Learning Workshop at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[397]

B. M. G. Nielsen • L. Gresele • A. Dittadi
Challenges in Explaining Representational Similarity through Identifiability.
UniReps @NeurIPS 2024 - 2nd Workshop on Unifying Representations in Neural Models at the 37th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[396]

J. Herbinger • M. N. Wright • T. Nagler • B. Bischl • G. Casalicchio
Decomposing Global Feature Effects Based on Feature Interactions.
Journal of Machine Learning Research 25.381. Dec. 2024. URL

[395]

L. Kook • P. F. M. Baumann • O. Dürr • B. Sick • D. Rügamer
Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo.
Journal of Statistical Software 111.10. Dec. 2024. DOI

[394]

J. Senoner • S. Schallmoser • B. Kratzwald • S. Feuerriegel • T. Netland
Explainable AI improves task performance in human–AI collaboration.
Scientific Reports 14.31150. Dec. 2024. DOI

[393]

C. Sauer • A.-L. Boulesteix • L. Hanßum • F. Hodiamont • C. Bausewein • T. Ullmann
Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications.
Preprint (Dec. 2024). arXiv

[392]

E. Garces Arias • J. Rodemann • M. Li • C. Heumann • M. Aßenmacher
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI

[391]

A. Bashardoust • S. Feuerriegel • Y. R. Shrestha
Comparing the Willingness to Share for Human-generated vs. AI-generated Fake News.
CSCW 2024 - 27th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. San José, Costa Rica, Nov 09-13, 2024. DOI

[390]

D. Geißler • S. Feuerriegel
Analyzing the Strategy of Propaganda using Inverse Reinforcement Learning: Evidence from the 2022 Russian Invasion of Ukraine.
CSCW 2024 - 27th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. San José, Costa Rica, Nov 09-13, 2024. DOI

[389]

A. Maarouf • N. Pröllochs • S. Feuerriegel
The Virality of Hate Speech on Social Media.
CSCW 2024 - 27th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. San José, Costa Rica, Nov 09-13, 2024. DOI

[388]

T. Woehrle • F. Pfeiffer • M. M. Mandl • W. Sobtzick • J. Heitzer • A. Krstova • L. Kamm • M. Feuerecker • D. Moser • M. Klein • B. Aulinger • M. Dolch • A.-L. Boulesteix • D. Lanz • A. Choukér
Point-of-care breath sample analysis by semiconductor-based E-Nose technology discriminates non-infected subjects from SARS-CoV-2 pneumonia patients: a multi-analyst experiment.
MedComm 5.11. Nov. 2024. DOI

[387]

Y. Li • Y. Zhang • K. Kawaguchi • A. Khakzar • B. Bischl • M. Rezaei
A Dual-Perspective Approach to Evaluating Feature Attribution Methods.
Transactions on Machine Learning Research. Nov. 2024. URL

[386]

D. Bär • A. Maarouf • S. Feuerriegel
Generative AI may backfire for counterspeech.
Preprint (Nov. 2024). arXiv

[385]

K. Flöge • M. A. Moeed • V. Fortuin
Stein Variational Newton Neural Network Ensembles.
Preprint (Nov. 2024). arXiv

[384]

J. Gauss • T. Nagler
Asymptotics for estimating a diverging number of parameters -- with and without sparsity.
Preprint (Nov. 2024). arXiv

[383]

P. Janetzky • T. Schlagenhauf • S. Feuerriegel
Slowing Down Forgetting in Continual Learning.
Preprint (Nov. 2024). arXiv

[382]

J. Nam • I. Chalkidis • M. Rezaei
Hyperbolic Contrastive Learning for Document Representations – A Multi-View Approach with Paragraph-level Similarities.
ECAI 2024 - 27th European Conference on Artificial Intelligence. Santiago de Compostela, Spain, Oct 19-24, 2024. DOI

[381]

M. Aßenmacher • L. Karrlein • P. Schiele • C. Heumann
Introducing wwm-german-18k - Can LLMs Crack the Million? (Or Win at Least 500 Euros?).
ICNLSP 2024 - 7th International Conference on Natural Language and Speech Processing. Trento, Italy, Oct 19-20, 2024. URL

[380]

J. Gertheiss • D. Rügamer • B. X. Liew • S. Greven
Functional Data Analysis: An Introduction and Recent Developments.
Biometrical Journal 66.7. Oct. 2024. DOI GitHub

[379]

Y. Ozyurt • S. Feuerriegel • M. Sachan
Automated Knowledge Concept Annotation and Question Representation Learning for Knowledge Tracing.
Preprint (Oct. 2024). arXiv

[378]

Y. Ozyurt • S. Feuerriegel • C. Zhang
Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language Models.
Preprint (Oct. 2024). arXiv

[377]

N. Sturma
Identifiability and Statistical Inference in Latent Variable Modeling.
Dissertation TU München. Sep. 2024. URL

[376]

Y. Liang • O. Zadorozhnyi • M. Drton
Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models.
PGM 2024 - 12th International Conference on Probabilistic Graphical Models. Nijmegen, The Netherlands, Sep 11-13, 2024. URL

[375]

D. Strieder • M. Drton
Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity.
PGM 2024 - 12th International Conference on Probabilistic Graphical Models. Nijmegen, The Netherlands, Sep 11-13, 2024. URL

[374]

H. Baniecki • G. Casalicchio • B. Bischl • P. Biecek
On the Robustness of Global Feature Effect Explanations.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[373]

F. Stermann • I. Chalkidis • A. Vahidi • B. Bischl • M. Rezaei
Attention-Driven Dropout: A Simple Method to Improve Self-supervised Contrastive Sentence Embeddings.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[372]

A. Vahidi • L. Wimmer • H. A. Gündüz • B. Bischl • E. Hüllermeier • M. Rezaei
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[371]

C. Molnar • G. König • B. Bischl • G. Casalicchio
Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach.
Data Mining and Knowledge Discovery 38. Sep. 2024. DOI

[370]

L. Barreñada • P. Dhiman • D. Timmerman • A.-L. Boulesteix • B. Van Calster
Understanding overfitting in random forest for probability estimation: a visualization and simulation study.
Diagnostic and Prognostic Research 8.14. Sep. 2024. DOI

[369]

Y. Li • T. Herold • U. Mansmann • R. Hornung
Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study.
Earth System Science Data 24.244. Sep. 2024. DOI

[368]

H. J. Coyle-Asbil • L. Burk • M. Brandes • B. Brandes • C. Buck • M. N. Wright • L. A. Vallis
Energy Expenditure Prediction in Preschool Children: A Machine Learning Approach Using Accelerometry and External Validation.
Physiological Measurement 45.9. Sep. 2024. DOI

[367]

D. Tschernutter • M. Kraus • S. Feuerriegel
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions.
Transactions on Machine Learning Research. Sep. 2024. URL

[366]

R. Hornung • A. Hapfelmeier
Multi forests: Variable importance for multi-class outcomes.
Preprint (Sep. 2024). arXiv

[365]

M. Kuzmanovic • D. Frauen • T. Hatt • S. Feuerriegel
Causal Machine Learning for Cost-Effective Allocation of Development Aid.
KDD 2024 - 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Barcelona, Spain, Aug 25-29, 2024. DOI

[364]

S. Urchs • V. Thurner • M. Aßenmacher • C. Heumann • S. Thiemichen
Detecting Gender Discrimination on Actor Level Using Linguistic Discourse Analysis.
GeBNLP 2024 - 5th Workshop on Gender Bias in Natural Language Processing. Bangkok, Thailand, Aug 16, 2024. DOI

[363]

A. Maarouf • D. Bär • D. Geißler • S. Feuerriegel
HQP: A human-annotated dataset for detecting online propaganda.
Findings @ACL 2024 - Findings of the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024. DOI

[362]

J. Pavlopoulos • V. Kougia • E. Garces Arias • P. Platanou • S. Shabalin • K. Liagkou • E. Papadatos • H. Essler • J.-B. Camps • F. Fischer
Challenging Error Correction in Recognised Byzantine Greek.
ML4AL @ACL 2024 - 1st Workshop on Machine Learning for Ancient Languages at the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024. DOI

[361]

M. Aßenmacher • A. Stephan • L. Weissweiler • E. Çano • I. Ziegler • M. Härttrich • B. Bischl • B. Roth • C. Heumann • H. Schütze
Collaborative Development of Modular Open Source Educational Resources for Natural Language Processing.
TeachingNLP @ACL 2024 - 6th Workshop on Teaching NLP at the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024. URL

[360]

J. G. Wiese • L. Wimmer • T. Papamarkou • B. Bischl • S. Günnemann • D. Rügamer
Towards Efficient Posterior Sampling in Deep Neural Networks via Symmetry Removal (Extended Abstract).
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI

[359]

L. Bothmann • K. Peters
Fairness als Qualitätskriterium im Maschinellen Lernen – Rekonstruktion des philosophischen Konzepts und Implikationen für die Nutzung außergesetzlicher Merkmale bei qualifizierten Mietspiegeln.
AStA Wirtschafts- und Sozialstatistisches Archiv 18. Aug. 2024. DOI

[358]

D. Schalk • R. Rehms • V. S. Hoffmann • B. Bischl • U. Mansmann
Distributed non-disclosive validation of predictive models by a modified ROC-GLM.
BMC Medical Research Methodology 24.190. Aug. 2024. DOI

[357]

F. Drost • E. Dorigatti • A. Straub • P. Hilgendorf • K. I. Wagner • K. Heyer • M. López Montes • B. Bischl • D. H. Busch • K. Schober • B. Schubert
Predicting T cell receptor functionality against mutant epitopes.
Cell Genomics 4.9. Aug. 2024. DOI

[356]

A. Mittermeier • M. Aßenmacher • B. Schachtner • S. Grosu • V. Dakovic • V. Kandratovich • B. Sabel • M. Ingrisch
Automatische ICD-10-Codierung.
Die Radiologie 64. Aug. 2024. DOI

[355]

F. Ott • L. Heublein • D. Rügamer • B. Bischl • C. Mutschler
Fusing structure from motion and simulation-augmented pose regression from optical flow for challenging indoor environments.
Journal of Visual Communication and Image Representation 103. Aug. 2024. DOI

[354]

E. Bergman • M. Feurer • A. Bahram • A. R. Balef • L. Purucker • S. Segel • M. Lindauer • F. Hutter • K. Eggensperger
AMLTK: A Modular AutoML Toolkit in Python.
The Journal of Open Source Software 9.100. Aug. 2024. DOI

[353]

R. Baptista • B. Liew • S. Pizzocaro • X. Zhai • S. Galasso • D. Rügamer • T. Waterkeyn • I. Boukhennoufa • X. Zhu • A. M. Nunzio
Motion Analysis in Neurological Rehabilitation: From the Lab to the Clinic.
Translational Neurorehabilitation. Aug. 2024. DOI

[352]

D. Schkoda • E. Robeva • M. Drton
Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding.
Preprint (Aug. 2024). arXiv

[351]

L. Bothmann • K. Peters • S. Dandl • M. Schomaker • B. Bischl
Causal Fair Machine Learning.
Statistical Computing 2024 - 54. Arbeitstagung der Arbeitsgruppen Statistical Computing, Klassifikation und Datenanalyse in den Biowissenschaften. Günzburg, Germany, Jul 28-31, 2024. PDF

[350]

L. Burk • J. Zobolas • B. Bischl • A. Bender • M. N. Wright • R. Sonabend
A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data.
Statistical Computing 2024 - 54. Arbeitstagung der Arbeitsgruppen Statistical Computing, Klassifikation und Datenanalyse in den Biowissenschaften. Günzburg, Germany, Jul 28-31, 2024. PDF

[349]

M. Herrmann
Dimensionality and Distance: Curse or Blessing? Geometrical Aspects of Nearest Neighbor Computation in High-Dimensional Data.
Statistical Computing 2024 - 54. Arbeitstagung der Arbeitsgruppen Statistical Computing, Klassifikation und Datenanalyse in den Biowissenschaften. Günzburg, Germany, Jul 28-31, 2024. PDF

[348]

K. Bouchiat • A. Immer • H. Yèche • G. Ratsch • V. Fortuin
Improving Neural Additive Models with Bayesian Principles.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[347]

D. Frauen • V. Melnychuk • S. Feuerriegel
Fair Off-Policy Learning from Observational Data.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[346]

M. Herrmann • F. J. D. Lange • K. Eggensperger • G. Casalicchio • M. Wever • M. Feurer • D. Rügamer • E. Hüllermeier • A.-L. Boulesteix • B. Bischl
Position: Why We Must Rethink Empirical Research in Machine Learning.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[345]

F. Karl • M. Kemeter • G. Dax • P. Sierak
Position: Embracing Negative Results in Machine Learning.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[344]

M. Lindauer • F. Karl • A. Klier • J. Moosbauer • A. Tornede • A. C. Mueller • F. Hutter • M. Feurer • B. Bischl
Position: A Call to Action for a Human-Centered AutoML Paradigm.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[343]

T. Papamarkou • M. Skoularidou • K. Palla • L. Aitchison • J. Arbel • D. Dunson • M. Filippone • V. Fortuin • P. Hennig • J. M. Hernández-Lobato • A. Hubin • A. Immer • T. Karaletsos • M. E. Khan • A. Kristiadi • Y. Li • S. Mandt • C. Nemeth • M. A. Osborne • T. G. J. Rudner • D. Rügamer • Y. W. Teh • M. Welling • A. G. Wilson • R. Zhang
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[342]

D. Rügamer • C. Kolb • T. Weber • L. Kook • T. Nagler
Generalizing orthogonalization for models with non-linearities.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[341]

J. Schweisthal • D. Frauen • M. Van der Schaar • S. Feuerriegel
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[340]

E. Sommer • L. Wimmer • T. Papamarkou • L. Bothmann • B. Bischl • D. Rügamer
Connecting the Dots: Is Mode Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[339]

D. Tramontano • Y. Kivva • S. Salehkaleybar • M. Drton • N. Kiyavash
Causal Effect Identification in LiNGAM Models with Latent Confounders.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[338]

S. Dandl • K. Blesch • T. Freiesleben • G. König • J. Kapar • B. Bischl • M. N. Wright
CountARFactuals – Generating plausible model-agnostic counterfactual explanations with adversarial random forests.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI

[337]

F. K. Ewald • L. Bothmann • M. N. Wright • B. Bischl • G. Casalicchio • G. König
A Guide to Feature Importance Methods for Scientific Inference.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI

[336]

D. Rundel • J. Kobialka • C. von Crailsheim • M. Feurer • T. Nagler • D. Rügamer
Interpretable Machine Learning for TabPFN.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI GitHub

[335]

C. A. Scholbeck • H. Funk • G. Casalicchio
Algorithm-Agnostic Feature Attributions for Clustering.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI

[334]

S. Dandl • M. Becker • B. Bischl • G. Casalicchio • L. Bothmann
mlr3summary: Concise and interpretable summaries for machine learning models.
xAI 2024 - Demo Track of the 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. arXiv

[333]

L. Kook • C. Kolb • P. Schiele • D. Dold • M. Arpogaus • C. Fritz • P. Baumann • P. Kopper • T. Pielok • E. Dorigatti • D. Rügamer
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.
UAI 2024 - 40th Conference on Uncertainty in Artificial Intelligence. Barcelona, Spain, Jul 16-18, 2024. URL

[332]

Y. Sale • P. Hofman • T. Löhr • L. Wimmer • T. Nagler • E. Hüllermeier
Label-wise Aleatoric and Epistemic Uncertainty Quantification.
UAI 2024 - 40th Conference on Uncertainty in Artificial Intelligence. Barcelona, Spain, Jul 16-18, 2024. URL

[331]

J. Piller • H. Küchenhoff • A. Bender
Flexible additive models for multi-event survival analysis.
IWSM 2024 - 38th International Workshop on Statistical Modelling. Durham, UK, Jul 14-19, 2024. PDF

[330]

S. Dandl • M. Becker • B. Bischl • G. Casalicchio • L. Bothmann
mlr3summary: Concise and interpretable summaries for machine learning models.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-11, 2024. arXiv GitHub

[329]

S. F. Fischer • M. Binder
mlr3torch - Deep Learning in R.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-11, 2024. GitHub

[328]

M. M. Mandl • A. S. Becker-Pennrich • L. C. Hinske • S. Hoffmann • A.-L. Boulesteix
Addressing researcher degrees of freedom through minP adjustment.
BMC Medical Research Methodology 24.152. Jul. 2024. DOI

[327]

B. Ronval • S. Nijssen • L. Bothmann
Can generative AI-based data balancing mitigate unfairness issues in Machine Learning?
EWAF 2024 - 3rd European Workshop on Algorithmic Fairness. Mainz, Germany, Jul 01-03, 2024. PDF

[326]

F. Karl • J. Thomas • J. Elstner • R. Gross • B. Bischl
Automated Machine Learning.
Unlocking Artificial Intelligence. Jul. 2024. DOI

[325]

D. Köhler • D. Rügamer • M. Schmid
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects.
Preprint (Jul. 2024). arXiv

[324]

F. Sergeev • P. Malsot • G. Rätsch • V. Fortuin
Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information.
Preprint (Jul. 2024). arXiv

[323]

C. F. Naumzik • A. Kongsted • W. Vach • S. Feuerriegel
Data-driven subgrouping of patient trajectories with chronic diseases: Evidence from low back pain.
CHIL 2024 - 5th AHLI Conference on Health, Inference, and Learning . New York City, NY, USA, Jun 27-28, 2024. URL

[322]

B. Deiseroth • M. Meuer • N. Gritsch • C. Eichenberg • P. Schramowski • M. Aßenmacher • K. Kersting
Divergent Token Metrics: Measuring degradation to prune away LLM components -- and optimize quantization.
NAACL 2024 - Annual Conference of the North American Chapter of the Association for Computational Linguistics. Mexico City, Mexico, Jun 16-21, 2024. DOI

[321]

H. Chen • J. Büssing • D. Rügamer • E. Nie
Leveraging (Sentence) Transformer Models with Contrastive Learning for Identifying Machine-Generated Text.
SemEval @NAACL 2024 - 18th International Workshop on Semantic Evaluation at the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Mexico City, Mexico, Jun 16-21, 2024. DOI

[320]

M. Aßenmacher • N. Sauter • C. Heumann
Classifying multilingual party manifestos: Domain transfer across country, time, and genre.
SwissText 2024 - Swiss Text Analytics Conference. Chur, Switzerland, Jun 10-11, 2024. URL

[319]

L. Mayer • C. Heumann • M. Aßenmacher
Can OpenSource beat ChatGPT? - A Comparative Study of Large Language Models for Text-to-Code Generation.
SwissText 2024 - Swiss Text Analytics Conference. Chur, Switzerland, Jun 10-11, 2024. URL

[318]

B. Säfken • D. Rügamer
Editorial special issue: Bridging the gap between AI and Statistics.
Advances in Statistical Analysis 108. Jun. 2024. DOI

[317]

K. Göbler • M. Drton • S. Mukherjee • A. Miloschewski
High-dimensional undirected graphical models for arbitrary mixed data.
Electronic Journal of Statistics 18.1. Jun. 2024. DOI

[316]

D. Bär • F. Pierri • G. De Francisci Morales • S. Feuerriegel
Systematic discrepancies in the delivery of political ads on facebook and instagram.
PNAS Nexus.pgae247. Jun. 2024. DOI

[315]

J. Ramjith • A. Bender • K. C. B. Roes • M. A. Jonker
Recurrent events analysis with piece-wise exponential additive mixed models.
Statistical Modelling 24.3. Jun. 2024. DOI

[314]

B. Felderer • L. Repke • W. Weber • J. Schweisthal • L. Bothmann
Predicting the Validity and Reliability of Survey Questions.
Preprint (Jun. 2024). DOI

[313]

E. Dorigatti
Cancer immunotherapy design and analysis through discrete optimization, positive-unlabeled learning, and semi-structured regression models.
Dissertation LMU München. May. 2024. DOI

[312]

C. A. Scholbeck
Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations.
Dissertation LMU München. May. 2024. DOI

[311]

K. Röck
Stochastic processes as surrogate models for dynamical systems in magnetic confinement fusion.
Dissertation LMU München. May. 2024. DOI

[310]

R. Kohli • M. Feurer • B. Bischl • K. Eggensperger • F. Hutter
Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning.
DMLR @ICLR 2024 - Workshop on Data-centric Machine Learning Research at the 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[309]

D. Frauen • F. Imrie • A. Curth • V. Melnychuk • S. Feuerriegel • M. van der Schaar
A Neural Framework for Generalized Causal Sensitivity Analysis.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[308]

K. Heß • V. Melnychuk • D. Frauen • S. Feuerriegel
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[307]

V. Melnychuk • D. Frauen • S. Feuerriegel
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[306]

M. Schröder • D. Frauen • S. Feuerriegel
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[305]

A. Vahidi • S. Schosser • L. Wimmer • Y. Li • B. Bischl • E. Hüllermeier • M. Rezaei
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL GitHub

[304]

D. Dold • D. Rügamer • B. Sick • O. Dürr
Bayesian Semi-structured Subspace Inference.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL

[303]

N. Palm • T. Nagler
An Online Bootstrap for Time Series.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL

[302]

D. Rügamer
Scalable Higher-Order Tensor Product Spline Models.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL

[301]

A. Solderer • S. P. Hicklin • M. Aßenmacher • A. Ender • P. R. Schmidlin
Influence of an allogenic collagen scaffold on implant sites with thin supracrestal tissue height: a randomized clinical trial.
Clinical Oral Investigations 28.313. May. 2024. DOI

[300]

K. Jeblick • B. Schachtner • J. Dexl • A. Mittermeier • A. T. Stüber • J. Topalis • T. Weber • P. Wesp • B. O. Sabel • J. Ricke • M. Ingrisch
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports.
European Radiology 34. May. 2024. DOI

[299]

A. F. Thielmann • A. Reuter • T. Kneib • D. Rügamer • B. Säfken
Interpretable Additive Tabular Transformer Networks.
Transactions on Machine Learning Research. May. 2024. URL

[298]

R. Debelak • T. Koch • M. Aßenmacher • C. Stachl
From Embeddings to Explainability: A Tutorial on Transformer-Based Text Analysis for Social and Behavioral Scientists.
Preprint (May. 2024). DOI

[297]

K. Heß • D. Frauen • V. Melnychuk • S. Feuerriegel
G-Transformer for Conditional Average Potential Outcome Estimation over Time.
Preprint (May. 2024). arXiv

[296]

P. Dettling • M. Drton • M. Kolar
On the Lasso for Graphical Continuous Lyapunov Models.
CLeaR 2024 - 3rd Conference on Causal Learning and Reasoning. Los Angeles, CA, USA, Apr 01-03, 2024. URL

[295]

K. Göbler • T. Windisch • M. Drton • T. Pychynski • M. Roth • S. Sonntag
causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery.
CLeaR 2024 - 3rd Conference on Causal Learning and Reasoning. Los Angeles, CA, USA, Apr 01-03, 2024. URL

[294]

D. Strieder • M. Drton
Dual Likelihood for Causal Inference under Structure Uncertainty.
CLeaR 2024 - 3rd Conference on Causal Learning and Reasoning. Los Angeles, CA, USA, Apr 01-03, 2024. URL

[293]

H. A. Gündüz • R. Mreches • J. Moosbauer • G. Robertson • X.-Y. To • E. A. Franzosa • C. Huttenhower • M. Rezaei • A. C. McHardy • B. Bischl • P. C. Münch • M. Binder
Optimized model architectures for deep learning on genomic data.
Communications Biology 7.1. Apr. 2024. DOI

[292]

M. Herrmann • D. Kazempour • F. Scheipl • P. Kröger
Enhancing cluster analysis via topological manifold learning.
Data Mining and Knowledge Discovery 38. Apr. 2024. DOI

[291]

S. Feuerriegel • D. Frauen • V. Melnychuk • J. Schweisthal • K. Heß • A. Curth • S. Bauer • N. Kilbertus • I. S. Kohane • M. van der Schaar
Causal machine learning for predicting treatment outcomes.
Nature Medicine 30. Apr. 2024. DOI

[290]

G. S. Collins • K. G. M. Moons • P. Dhiman • R. D. Riley • A. L. Beam • B. Van Calster • M. Ghassemi • X. Liu • J. B. Reitsma • M. van Smeden • A.-L. Boulesteix • J. C. Camaradou • L. A. Celi • S. Denaxas • A. K. Denniston • B. Glocker • R. M. Golub • H. Harvey • G. Heinze • M. M. Hoffman • A. P. Kengne • E. Lam • N. Lee • E. W. Loder • L. Maier-Hein • B. A. Mateen • M. D. McCradden • L. Oakden-Rayner • J. Ordish • R. Parnell • S. Rose • K. Singh • L. Wynants • P. Logullo
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.
The BMJ 385.e078378. Apr. 2024. DOI

[289]

C. Gruber • K. Hechinger • M. Aßenmacher • G. Kauermann • B. Plank
More Labels or Cases? Assessing Label Variation in Natural Language Inference.
UnImplicit 2024 - 3rd Workshop on Understanding Implicit and Underspecified Language. Malta, Mar 21, 2024. URL

[288]

S. Dandl • C. Haslinger • T. Hothorn • H. Seibold • E. Sverdrup • S. Wager • A. Zeileis
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Annals of Applied Statistics 18.1. Mar. 2024. DOI

[287]

F. Coens • N. Knops • I. Tieken • S. Vogelaar • A. Bender • J. J. Kim • K. Krupka • L. Pape • A. Raes • B. Tönshoff • A. Prytula • C. Registry
Time-Varying Determinants of Graft Failure in Pediatric Kidney Transplantation in Europe.
Clinical Journal of the American Society of Nephrology 19.3. Mar. 2024. DOI

[286]

W. H. Hartl • P. Kopper • L. Xu • L. Heller • M. Mironov • R. Wang • A. G. Day • G. Elke • H. Küchenhoff • A. Bender
Relevance of Protein Intake for Weaning in the Mechanically Ventilated Critically Ill: Analysis of a Large International Database.
Critical Care Medicine 50.3. Mar. 2024. DOI

[285]

M. Maritsch • S. Föll • V. Lehmann • N. Styger • C. Bérubé • M. Kraus • S. Feuerriegel • T. Kowatsch • T. Züger • E. Fleisch • F. Wortmann • C. Stettler
Smartwatches for non-invasive hypoglycaemia detection during cognitive and psychomotor stress.
Diabetes, Obesity and Metabolism 26.3. Mar. 2024. DOI

[284]

B. X. Liew • F. Pfisterer • D. Rügamer • X. Zhai
Strategies to optimise machine learning classification performance when using biomechanical features.
Journal of Biomechanics 165. Mar. 2024. DOI

[283]

N. Sturma • M. Drton • D. Leung
Testing many constraints in possibly irregular models using incomplete U-statistics.
Journal of the Royal Statistical Society. Series B (Statistical Methodology) 86.4. Mar. 2024. DOI

[282]

J. Gertheiss • D. Rügamer • S. Greven
Methoden für die Analyse funktionaler Daten.
Moderne Verfahren der Angewandten Statistik. Mar. 2024. DOI

[281]

M. M. Mandl • S. Hoffmann • S. Bieringer • A. E. Jacob • M. Kraft • S. Lemster • A.-L. Boulesteix
Raising awareness of uncertain choices in empirical data analysis: A teaching concept toward replicable research practices.
PLOS Computational Biology 20.3. Mar. 2024. DOI

[280]

S. Dandl • A. Bender • T. Hothorn
Heterogeneous treatment effect estimation for observational data using model-based forests.
Statistical Methods in Medical Research 33.3. Mar. 2024. DOI

[279]

A. Reuter • B. Khadka • A. Thielmann • C. Weisser • S. F. Fischer • B. Säfken
GPTopic: Dynamic and Interactive Topic Representations.
Preprint (Mar. 2024). arXiv GitHub

[278]

S. Wiegrebe • P. Kopper • R. Sonabend • B. Bischl • A. Bender
Deep learning for survival analysis: a review.
Artificial Intelligence Review 57.65. Feb. 2024. DOI

[277]

S. Feuerriegel • J. Hartmann • C. Janiesch • P. Zschech
Generative AI.
Business and Information Systems Engineering 66.1. Feb. 2024. DOI

[276]

C. A. Scholbeck • G. Casalicchio • C. Molnar • B. Bischl • C. Heumann
Marginal Effects for Non-Linear Prediction Functions.
Data Mining and Knowledge Discovery 38. Feb. 2024. DOI

[275]

B. X. W. Liew • D. Rügamer • A. V. Birn-Jeffery
Neuromechanical stabilisation of the centre of mass during running.
Gait and Posture 108. Feb. 2024. DOI

[274]

H. Weerts • F. Pfisterer • M. Feurer • K. Eggensperger • E. Bergman • N. Awad • J. Vanschoren • M. Pechenizkiy • B. Bischl • F. Hutter
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.
Journal of Artificial Intelligence Research 79. Feb. 2024. DOI

[273]

P. Gijsbers • M. L. P. Bueno • S. Coors • E. LeDell • S. Poirier • J. Thomas • B. Bischl • J. Vanschoren
AMLB: an AutoML Benchmark.
Journal of Machine Learning Research 25.101. Feb. 2024. URL

[272]

D. Schalk • B. Bischl • D. Rügamer
Privacy-Preserving and Lossless Distributed Estimation of High-Dimensional Generalized Additive Mixed Models.
Statistics and Computing 34.31. Feb. 2024. DOI

[271]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI

[270]

B. Bischl • R. Sonabend • L. Kotthoff • M. Lang
Applied Machine Learning Using mlr3 in R.
American Statistician 79.2. Jan. 2024. DOI

[269]

G. Casalicchio • L. Burk
Evaluation and Benchmarking.
Applied Machine Learning Using mlr3 in R I.3. Jan. 2024. DOI

[268]

M. Becker • L. Schneider • S. F. Fischer
Hyperparameter Optimization.
Applied Machine Learning Using mlr3 in R II.4. Jan. 2024. DOI

[267]

L. Schneider • M. Becker
Advanced Tuning Methods and Black Box Optimization.
Applied Machine Learning Using mlr3 in R II.5. Jan. 2024. DOI

[266]

M. Binder • F. Pfisterer
Sequential Pipelines.
Applied Machine Learning Using mlr3 in R II.7. Jan. 2024. DOI

[265]

M. Binder • F. Pfisterer • M. Becker • M. N. Wright
Non-sequential Pipelines and Tuning.
Applied Machine Learning Using mlr3 in R II.8. Jan. 2024. DOI

[264]

M. Lang • S. F. Fischer • R. Sonabend
Advanced Technical Aspects of mlr3.
Applied Machine Learning Using mlr3 in R IV.10. Jan. 2024. DOI

[263]

S. F. Fischer • M. Lang • M. Becker
Large-Scale Benchmarking.
Applied Machine Learning Using mlr3 in R IV.11. Jan. 2024. DOI

[262]

S. Dandl • P. Biecek • G. Casalicchio • M. N. Wright
Model Interpretation.
Applied Machine Learning Using mlr3 in R IV.12. Jan. 2024. DOI

[261]

C. Sauer • S. Hoffmann • T. Ullmann • A.-L. Boulesteix
Explaining the optimistic performance evaluation of newly proposed methods: A cross-design validation experiment.
Biometrical Journal 66.1. Jan. 2024. DOI

[260]

V. Lehmann • T. Zueger • M. Maritsch • M. Notter • S. Schallmoser • C. Bérubé • C. Albrecht • M. Kraus • S. Feuerriegel • E. Fleisch • T. Kowatsch • S. Lagger • M. Laimer • F. Wortmann • C. Stettler
Machine Learning to Infer a Health State Using Biomedical Signals - Detection of Hypoglycemia in People with Diabetes while Driving Real Cars.
NEJM AI. Jan. 2024. DOI

[259]

B. S. Siepe • F. Bartoš • T. P. Morris • A.-L. Boulesteix • D. W. Heck • S. Pawel
Simulation Studies for Methodological Research in Psychology: A Standardized Template for Planning, Preregistration, and Reporting.
Psychological Methods Advance online publication. Jan. 2024. DOI

[258]

Z. S. Dunias • B. Van Calster • D. Timmerman • A.-L. Boulesteix • M. van Smeden
A comparison of hyperparameter tuning procedures for clinical prediction models: A simulation study.
Statistics in Medicine. Jan. 2024. DOI

[257]

R. Hornung • F. Ludwigs • J. Hagenberg • A.-L. Boulesteix
Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study.
Wiley Interdisciplinary Reviews: Computational Statistics 16.1. Jan. 2024. DOI

[256]

M. Wünsch • C. Sauer • P. Callahan • L. C. Hinske • A.-L. Boulesteix
From RNA sequencing measurements to the final results: a practical guide to navigating the choices and uncertainties of gene set analysis.
Wiley Interdisciplinary Reviews: Computational Statistics 16.1. Jan. 2024. DOI

[255]

J. Goschenhofer
Reducing the effort for data annotation: contributions to weakly supervised deep learning.
Dissertation LMU München. Dec. 2023. DOI

[254]

H. A. Gündüz • S. Giri • M. Binder • B. Bischl • M. Rezaei
Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences.
ICMLA 2023 - 22nd IEEE International Conference on Machine Learning and Applications. Jacksonville, FL, USA, Dec 15-17, 2023. DOI

[253]

M. von Zahn • O. Hinz • S. Feuerriegel
Locating disparities in machine learning.
IEEE BigData 2023 - IEEE International Conference on Big Data. Sorrento, Italy, Dec 15-18, 2023. DOI

[252]

D. Frauen • V. Melnychuk • S. Feuerriegel
Sharp Bounds for Generalized Causal Sensitivity Analysis.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[251]

V. Melnychuk • D. Frauen • S. Feuerriegel
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[250]

J. Schweisthal • D. Frauen • V. Melnychuk • S. Feuerriegel
Reliable Off-Policy Learning for Dosage Combinations.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[249]

N. Sturma • C. Squires • M. Drton • C. Uhler
Unpaired Multi-Domain Causal Representation Learning.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[248]

Y. Zhang • Y. Li • H. Brown • M. Rezaei • B. Bischl • P. Torr • A. Khakzar • K. Kawaguchi
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments.
XAIA 2023 @NeurIPS 2023 - Workshop XAI in Action: Past, Present, and Future Applications at the 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. URL

[247]

Z. Zhang • H. Yang • B. Ma • D. Rügamer • E. Nie
Baby’s CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models.
BabyLM Challenge @CoNLL 2023) - 1st BabyLM Challenge at the 27th Conference on Computational Natural Language Learning. Singapore, Dec 06-10, 2023. DOI GitHub

[246]

S. Dandl
Causality concepts in machine learning: heterogeneous treatment effect estimation with machine learning and model interpretation with counterfactual and semi-factual explanations.
Dissertation LMU München. Dec. 2023. DOI

[245]

E. Garces Arias • V. Pai • M. Schöffel • C. Heumann • M. Aßenmacher
Automatic transcription of handwritten Old Occitan language.
EMNLP 2023 - Conference on Empirical Methods in Natural Language Processing. Singapore, Dec 06-10, 2023. DOI

[244]

J. Herbinger
On grouping and partitioning approaches in interpretable machine learning.
Dissertation LMU München. Dec. 2023. DOI

[243]

F. Karl • T. Pielok • J. Moosbauer • F. Pfisterer • S. Coors • M. Binder • L. Schneider • J. Thomas • J. Richter • M. Lang • E. C. Garrido-Merchán • J. Branke • B. Bischl
Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview.
ACM Transactions on Evolutionary Learning and Optimization 3.4. Dec. 2023. DOI

[242]

D. Geißler • D. Bär • N. Pröllochs • S. Feuerriegel
Russian propaganda on social media during the 2022 invasion of Ukraine.
EPJ Data Science. Dec. 2023. DOI

[241]

J. Rausch • G. Rashiti • M. Gusev • C. Zhang • S. Feuerriegel
DSG: An End-to-End Document Structure Generator.
ICDM 2023 - 23rd IEEE International Conference on Data Mining. Shanghai, China, Dec 01-04, 2023. DOI

[240]

C. Koller • G. Kauermann • X. Zhu
Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance in Earth Observation?
IEEE Transactions on Geoscience and Remote Sensing 62. Dec. 2023. DOI GitHub

[239]

A. T. Stüber • S. Coors • B. Schachtner • T. Weber • D. Rügamer • A. Bender • A. Mittermeier • O. Öcal • M. Seidensticker • J. Ricke • B. Bischl • M. Ingrisch
A comprehensive machine learning benchmark study for radiomics-based survival analysis of CT imaging data in patients with hepatic metastases of CRC.
Investigative Radiology 58.12. Dec. 2023. DOI

[238]

D. Strieder • M. Drton
Confidence in causal inference under structure uncertainty in linear causal models with equal variances.
Journal of Causal Inference 11.1. Dec. 2023. DOI

[237]

Y. Sale • P. Hofman • L. Wimmer • E. Hüllermeier • T. Nagler
Second-Order Uncertainty Quantification: Variance-Based Measures.
Preprint (Dec. 2023). arXiv

[236]

C. A. Scholbeck • J. Moosbauer • G. Casalicchio • H. Gupta • B. Bischl • C. Heumann
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis.
Preprint (Dec. 2023). arXiv

[235]

D. Rügamer • F. Pfisterer • B. Bischl • B. Grün
Mixture of Experts Distributional Regression: Implementation Using Robust Estimation with Adaptive First-order Methods.
Advances in Statistical Analysis. Nov. 2023. DOI

[234]

L. Bothmann • L. Wimmer • O. Charrakh • T. Weber • H. Edelhoff • W. Peters • H. Nguyen • C. Benjamin • A. Menzel
Automated wildlife image classification: An active learning tool for ecological applications.
Ecological Informatics 77. Nov. 2023. DOI

[233]

S. Feuerriegel • R. DiResta • J. A. Goldstein • S. Kumar • P. Lorenz-Spreen • M. Tomz • N. Pröllochs
Research can help to tackle AI-generated disinformation.
Nature Human Behaviour 7. Nov. 2023. DOI

[232]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings.
Preprint (Nov. 2023). arXiv

[231]

N. Pröllochs • S. Feuerriegel
Mechanisms of True and False Rumor Sharing in Social Media: Collective Intelligence or Herd Behavior?
CSCW 2024 - 26th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing. Minneapolis, MN, USA, Oct 24-18, 2023. DOI

[230]

G. König
If interpretability is the answer, what is the question?: a causal perspective.
Dissertation LMU München. Oct. 2023. DOI

[229]

M. Rezaei • F. Soleymani • B. Bischl • S. Azizi
Deep Bregman divergence for self-supervised representations learning.
Computer Vision and Image Understanding 235.103801. Oct. 2023. DOI

[228]

Y. R. Shrestha • G. von Krogh • S. Feuerriegel
Building open-source AI.
Nature Computational Science 3.11. Oct. 2023. DOI

[227]

J. Gauss • F. Scheipl • M. Herrmann
DCSI–An improved measure of cluster separability based on separation and connectedness.
Preprint (Oct. 2023). arXiv

[226]

Y. Ma • D. Frauen • V. Melnychuk • S. Feuerriegel
Counterfactual Fairness for Predictions using Generative Adversarial Networks.
Preprint (Oct. 2023). arXiv

[225]

I. Ziegler • B. Ma • B. Bischl • E. Dorigatti • B. Schubert
Proteasomal cleavage prediction: state-of-the-art and future directions.
Preprint (Oct. 2023). DOI GitHub

[224]

L. Bothmann • S. Dandl • M. Schomaker
Causal Fair Machine Learning via Rank-Preserving Interventional Distributions.
ECAI 2023 - 1st Workshop on Fairness and Bias in AI co-located with the 26th European Conference on Artificial Intelligence. Kraków, Poland, Sep 30-Oct 04, 2023. PDF

[223]

J. Herbinger • S. Dandl • F. K. Ewald • S. Loibl • G. Casalicchio
Leveraging Model-based Trees as Interpretable Surrogate Models for Model Distillation.
ECAI 2023 - 3rd International Workshop on Explainable and Interpretable Machine Learning co-located with the 26th European Conference on Artificial Intelligence. Kraków, Poland, Sep 30-Oct 04, 2023. DOI

[222]

S. Urchs • V. Thurner • M. Aßenmacher • C. Heumann • S. Thiemichen
How Prevalent is Gender Bias in ChatGPT? - Exploring German and English ChatGPT Responses.
BDCA @ECML-PKDD 2023 - 1st Workshop on Biased Data in Conversational Agents at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[221]

I. T. Öztürk • R. Nedelchev • C. Heumann • E. Garces Arias • M. Roger • B. Bischl • M. Aßenmacher
How Different Is Stereotypical Bias Across Languages?
BIAS @ECML-PKDD 2023 - 3rd Workshop on Bias and Fairness in AI at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[220]

S. Dandl • G. Casalicchio • B. Bischl • L. Bothmann
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[219]

L. Rauch • M. Aßenmacher • D. Huseljic • M. Wirth • B. Bischl • B. Sick
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[218]

J. G. Wiese • L. Wimmer • T. Papamarkou • B. Bischl • S. Günnemann • D. Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. Best Paper Award. DOI

[217]

M. Aßenmacher • L. Rauch • J. Goschenhofer • A. Stephan • B. Bischl • B. Roth • B. Sick
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering.
IAL @ECML-PKDD 2023 - 7th International Workshop on Interactive Adaptive Learning at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. PDF

[216]

L. O. Purucker • L. Schneider • M. Anastacio • J. Beel • B. Bischl • H. Hoos
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML.
AutoML 2023 - International Conference on Automated Machine Learning. Berlin, Germany, Sep 12-15, 2023. URL

[215]

S. Segel • H. Graf • A. Tornede • B. Bischl • M. Lindauer
Symbolic Explanations for Hyperparameter Optimization.
AutoML 2023 - International Conference on Automated Machine Learning. Berlin, Germany, Sep 12-15, 2023. URL

[214]

S. F. Fischer • L. Harutyunyan • M. Feurer • B. Bischl
OpenML-CTR23 - A curated tabular regression benchmarking suite.
Workshop @AutoML 2023 - Workshop at the International Conference on Automated Machine Learning. Berlin, Germany, Sep 12-15, 2023. URL

[213]

P. Koch • G. V. Nuñez • E. Garces Arias • C. Heumann • M. Schöffel • A. Häberlin • M. Aßenmacher
A tailored Handwritten-Text-Recognition System for Medieval Latin.
ALP @RANLP 2023 - 1st Workshop on Ancient Language Processing at the Conference on Recent Advances in Natural Language Processing. Varna, Bulgaria, Sep 08, 2023. URL

[212]

H. A. Gündüz • M. Binder • X.-Y. To • R. Mreches • B. Bischl • A. C. McHardy • P. C. Münch • M. Rezaei
A self-supervised deep learning method for data-efficient training in genomics.
Communications Biology 6.928. Sep. 2023. DOI

[211]

D. Bär • N. Pröllochs • S. Feuerriegel
New Threats to Society from Free-Speech Social Media Platforms.
Communications of the ACM 66.10. Sep. 2023. DOI

[210]

M. Toetzke • B. Probst • S. Feuerriegel
Leveraging large language models to monitor climate technology innovation.
Environmental Research Letters 18.9. Sep. 2023. DOI

[209]

B. X. W. Liew • F. M. Kovacs • D. Rügamer • A. Royuela
Automatic variable selection algorithms in prognostic factor research in neck pain.
Journal of Clinical Medicine. Sep. 2023. DOI

[208]

S. Hoffmann • F. Scheipl • A.-L. Boulesteix
Reproduzierbare und replizierbare Forschung.
Moderne Verfahren der Angewandten Statistik. Sep. 2023. DOI

[207]

R. P. Prager • K. Dietrich • L. Schneider • L. Schäpermeier • B. Bischl • P. Kerschke • H. Trautmann • O. Mersmann
Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features.
FOGA 2023 - 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. Potsdam, Germany, Aug 30-Sep 01, 2023. DOI

[206]

A. Scheppach • H. A. Gündüz • E. Dorigatti • P. C. Münch • A. C. McHardy • B. Bischl • M. Rezaei • M. Binder
Neural Architecture Search for Genomic Sequence Data.
CIBCB 2023 - 20th IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology. Eindhoven, The Netherlands, Aug 29-31, 2023. DOI

[205]

F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition.
IEEE Access 11. Aug. 2023. DOI

[204]

A. Volkmann • A. Stöcker • F. Scheipl • S. Greven
Multivariate Functional Additive Mixed Models.
Statistical Modelling 23.4. Aug. 2023. DOI

[203]

L. Fahrmeir • G. Kauermann • G. Tutz • M. Windmann
Spatial smoothing revisited: An application to rental data in Munich.
Statistical Modelling 23.5-6. Aug. 2023. DOI

[202]

F. Pfisterer • S. Wei • S. Vollmer • M. Lang • B. Bischl
Fairness Audits and Debiasing Using mlr3fairness.
The R Journal 15.1. Aug. 2023. DOI

[201]

J. Rodemann • J. Goschenhofer • E. Dorigatti • T. Nagler • T. Augustin
Approximately Bayes-optimal pseudo-label selection.
UAI 2023 - 39th Conference on Uncertainty in Artificial Intelligence. Pittsburgh, PA, USA, Jul 31-Aug 03, 2023. URL

[200]

L. Wimmer • Y. Sale • P. Hofman • B. Bischl • E. Hüllermeier
Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?
UAI 2023 - 39th Conference on Uncertainty in Artificial Intelligence. Pittsburgh, PA, USA, Jul 31-Aug 03, 2023. URL

[199]

C. Molnar • T. Freiesleben • G. König • J. Herbinger • T. Reisinger • G. Casalicchio • M. N. Wright • B. Bischl
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
xAI 2023 - 1st World Conference on eXplainable Artificial Intelligence. Lisbon, Portugal, Jul 26-28, 2023. DOI

[198]

V. Melnychuk • D. Frauen • S. Feuerriegel
Normalizing Flows for Interventional Density Estimation.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[197]

T. Nagler
Statistical Foundations of Prior-Data Fitted Networks.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[196]

D. Rügamer
A New PHO-rmula for Improved Performance of Semi-Structured Networks.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[195]

F. Ott
Representation learning for domain adaptation and cross-modal retrieval: in the context of online handwriting recognition and visual self-localization.
Dissertation LMU München. Jul. 2023. DOI

[194]

J. Goschenhofer • B. Bischl • Z. Kira
ConstraintMatch for Semi-constrained Clustering.
IJCNN 2023 - International Joint Conference on Neural Networks. Gold Coast Convention and Exhibition Centre, Queensland, Australia, Jul 18-23, 2023. DOI

[193]

C. Kolb • B. Bischl • C. L. Müller • D. Rügamer
Sparse Modality Regression.
IWSM 2023 - 37th International Workshop on Statistical Modelling. Dortmund, Germany, Jul 17-21, 2023. Best Paper Award. PDF

[192]

L. Schneider • B. Bischl • J. Thomas
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models.
GECCO 2023 - Genetic and Evolutionary Computation Conference. Lisbon, Portugal, Jul 15-19, 2023. DOI

[191]

D. Saggau • M. Rezaei • B. Bischl • I. Chalkidis
Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning.
Findings @ACL 2023 - Findings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada, Jul 09-14, 2023. DOI

[190]

B. X. W. Liew • D. Rügamer • Q. Mei • Z. Altai • X. Zhu • X. Zhai • N. Cortes
Smooth and accurate predictions of joint contact force timeseries in gait using overparameterised deep neural networks.
Frontiers in Bioengineering and Biotechnology 11. Jul. 2023. DOI

[189]

C. Fritz • G. De Nicola • S. Kevork • D. Harhoff • G. Kauermann
Modelling the large and dynamically growing bipartite network of German patents and inventors.
Journal of the Royal Statistical Society. Series A (Statistics in Society) 186.3. Jul. 2023. DOI

[188]

I. van Mechelen • A.-L. Boulesteix • R. Dangl • N. Dean • C. Hennig • F. Leisch • D. Steinley • M. J. Warrens
A white paper on good research practices in benchmarking: The case of cluster analysis.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13.6. Jul. 2023. DOI

[187]

C. Kolb • C. L. Müller • B. Bischl • D. Rügamer
Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization.
Preprint (Jul. 2023). arXiv

[186]

D. Bär • N. Pröllochs • S. Feuerriegel
Finding Qs: Profiling QAnon Supporters on Parler.
ICWSM 2023 - 17th International AAAI Conference on Web and Social Media. Limassol, Cyprus, Jun 05-08, 2023. DOI

[185]

S. Kaminwar • J. Goschenhofer • J. Thomas • I. Thon • B. Bischl
Structured Verification of Machine Learning Models in Industrial Settings.
Big Data 11.3. Jun. 2023. DOI

[184]

M. Rezaei • A. Vahidi • B. Bischl • T. Elze • M. Eslami
Self-supervised Learning and Self-labeling Framework for Glaucoma Detection.
Investigative Ophthalmology and Visual Science 64.8. Jun. 2023. URL

[183]

J. Moosbauer
Towards explainable automated machine learning.
Dissertation LMU München. May. 2023. DOI

[182]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI

[181]

K. Röck • D. Rügamer • B. Bischl • U. von Toussaint • C. G. Albert
Dependent state space Student-t processes for imputation and data augmentation in plasma diagnostics.
Contributions to Plasma Physics 63.5-6. May. 2023. DOI

[180]

D. Frauen • S. Feuerriegel
Estimating individual treatment effects under unobserved confounding using binary instruments.
ICLR 2023 - 11th International Conference on Learning Representations. Kigali, Rwanda, May 01-05, 2023. URL

[179]

T. Pielok • B. Bischl • D. Rügamer
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent.
ICLR 2023 - 11th International Conference on Learning Representations. Kigali, Rwanda, May 01-05, 2023. URL

[178]

N. Banholzer • T. Mellan • H. J. T. Unwin • S. Feuerriegel • S. Mishra • S. Bhatt
A comparison of short-term probabilistic forecasts for the incidence of COVID-19 using mechanistic and statistical time series models.
Preprint (May. 2023). arXiv

[177]

D. Bär • F. Calderon • M. Lawlor • S. Licklederer • M. Totzauer • S. Feuerriegel
Analyzing Social Media Activities at Bellingcat.
WebSci 2023 - 15th ACM Web Science Conference 2023. Austin, TX, USA, Apr 30-May 01, 2023. DOI

[176]

E. Dorigatti • B. Schubert • B. Bischl • D. Rügamer
Frequentist Uncertainty Quantification in Semi-Structured Neural Networks.
AISTATS 2023 - 26th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, Apr 25-27, 2023. URL

[175]

G. Keropyan • D. Strieder • M. Drton
Rank-Based Causal Discovery for Post-Nonlinear Models.
AISTATS 2023 - 26th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, Apr 25-27, 2023. URL

[174]

C. Luther • G. König • M. Grosse-Wentrup
Efficient SAGE Estimation via Causal Structure Learning.
AISTATS 2023 - 26th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, Apr 25-27, 2023. URL

[173]

M. Feurer • K. Eggensperger • E. Bergman • F. Pfisterer • B. Bischl • F. Hutter
Mind the Gap: Measuring Generalization Performance Across Multiple Objectives.
IDA 2023 - 21st International Symposium on Intelligent Data Analysis. Louvain-la-Neuve, Belgium, Apr 12-14, 2023. DOI

[172]

D. Schalk • B. Bischl • D. Rügamer
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization.
Journal of Computational and Graphical Statistics 32.2. Apr. 2023. DOI

[171]

M. Herrmann • F. Pfisterer • F. Scheipl
A geometric framework for outlier detection in high-dimensional data.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery e1491. Apr. 2023. DOI

[170]

D. Schalk
Modern approaches for component-wise boosting: Automation, efficiency, and distributed computing with application to the medical domain.
Dissertation LMU München. Mar. 2023. DOI

[169]

J. Moosbauer • G. Casalicchio • M. Lindauer • B. Bischl
Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution.
COSEAL 2023 - Workshop on Configuration and Selection of Algorithms. Paris, France, Mar 06-08, 2023. arXiv

[168]

T. Ullmann • A. Beer • M. Hünemörder • T. Seidl • A.-L. Boulesteix
Over-optimistic evaluation and reporting of novel cluster algorithms: An illustrative study.
Advances in Data Analysis and Classification 17. Mar. 2023. DOI

[167]

T. Nagler • T. Vatter
Solving Estimating Equations With Copulas.
Journal of the American Statistical Association 119.546. Mar. 2023. DOI

[166]

B. Bischl • M. Binder • M. Lang • T. Pielok • J. Richter • S. Coors • J. Thomas • T. Ullmann • M. Becker • A.-L. Boulesteix • D. Deng • M. Lindauer
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13.2. Mar. 2023. DOI

[165]

D. Frauen • T. Hatt • V. Melnychuk • S. Feuerriegel
Estimating Average Causal Effects from Patient Trajectories.
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI

[164]

G. König • T. Freiesleben • M. Grosse-Wentrup
Improvement-focused causal recourse (ICR).
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI

[163]

D. Rügamer • C. Kolb • N. Klein
Semi-Structured Distributional Regression.
American Statistician. Feb. 2023. DOI

[162]

S. Schallmoser • T. Zueger • M. Kraus • M. Saar-Tsechansky • C. Stettler • S. Feuerriegel
Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study.
Journal of Medical Internet Research 25. Feb. 2023. DOI

[161]

D. Rügamer • P. Baumann • T. Kneib • T. Hothorn
Probabilistic Time Series Forecasts with Autoregressive Transformation Models.
Statistics and Computing 33.2. Feb. 2023. DOI

[160]

D. Schalk • V. S. Hoffmann • B. Bischl • U. Mansmann
dsBinVal: Conducting distributed ROC analysis using DataSHIELD.
The Journal of Open Source Software 8.82. Feb. 2023. DOI

[159]

D. Rügamer
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods.
Preprint (Feb. 2023). arXiv

[158]

T. Ullmann • S. Peschel • P. Finger • C. L. Müller • A.-L. Boulesteix
Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering.
PLOS Computational Biology 19.1. Jan. 2023. DOI

[157]

J. Goschenhofer • P. Ragupathy • C. Heumann • B. Bischl • M. Aßenmacher
CC-Top: Constrained Clustering for Dynamic Topic Discovery.
EvoNLP 2022 - 1st Workshop on Ever Evolving NLP. Abu Dhabi, United Arab Emirates, Dec 07, 2022. DOI

[156]

T. Ullmann
Evaluation of clustering results and novel cluster algorithms: a metascientific perspective.
Dissertation LMU München. Dec. 2022. DOI

[155]

R. Foygel Barber • M. Drton • N. Sturma • L. Weihs
Half-trek criterion for identifiability of latent variable models.
Annals of Statistics 50.6. Dec. 2022. DOI

[154]

K. Lotto • T. Nagler • M. Radic
Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving.
Electronics 11.24. Dec. 2022. DOI

[153]

F. Ott • D. Rügamer • L. Heublein • T. Hamann • J. Barth • B. Bischl • C. Mutschler
Benchmarking online sequence-to-sequence and character-based handwriting recognition from IMU-enhanced pens.
International Journal on Document Analysis and Recognition 25.4. Dec. 2022. DOI

[152]

C. Fritz • G. De Nicola • F. Günther • D. Rügamer • M. Rave • M. Schneble • A. Bender • M. Weigert • R. Brinks • A. Hoyer • U. Berger • H. Küchenhoff • G. Kauermann
Challenges in Interpreting Epidemiological Surveillance Data – Experiences from Germany.
Journal of Computational and Graphical Statistics 32.3. Dec. 2022. DOI

[151]

M. Rezaei • E. Dorigatti • D. Rügamer • B. Bischl
Joint Debiased Representation Learning and Imbalanced Data Clustering.
Workshop @ICDM 2022 - Workshop at the 22nd IEEE International Conference on Data Mining. Orlando, FL, USA, Nov 30-Dec 02, 2022. DOI

[150]

N. Hurmer • X.-Y. To • M. Binder • H. A. Gündüz • P. C. Münch • R. Mreches • A. C. McHardy • B. Bischl • M. Rezaei
Transformer Model for Genome Sequence Analysis.
LMRL @NeurIPS 2022 - Workshop on Learning Meaningful Representations of Life at the 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

[149]

I. Ziegler • B. Ma • E. Nie • B. Bischl • D. Rügamer • B. Schubert • E. Dorigatti
What cleaves? Is proteasomal cleavage prediction reaching a ceiling?
LMRL @NeurIPS 2022 - Workshop on Learning Meaningful Representations of Life at the 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

[148]

E. Pretzsch • V. Heinemann • S. Stintzing • A. Bender • S. Chen • J. W. Holch • F. O. Hofmann • H. Ren • F. Böschand • H. Küchenhoff • J. Werner • M. K. Angele
EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3).
Cancers 14.22. Nov. 2022. DOI

[147]

M. Herrmann
Towards more reliable machine learning: conceptual insights and practical approaches for unsupervised manifold learning and supervised benchmark studies.
Dissertation LMU München. Oct. 2022. DOI

[146]

F. Pfisterer
Democratizing machine learning: contributions in AutoML and fairness.
Dissertation LMU München. Oct. 2022. DOI

[145]

F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift.
MM 2022 - 30th ACM International Conference on Multimedia. Lisbon, Portugal, Oct 10-14, 2022. DOI

[144]

N. Palm • F. Stroebl • H. Palm
Parameter Individual Optimal Experimental Design and Calibration of Parametric Models.
IEEE Access 10. Oct. 2022. DOI GitHub

[143]

J. Moosbauer • M. Binder • L. Schneider • F. Pfisterer • M. Becker • M. Lang • L. Kotthoff • B. Bischl
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers.
IEEE Transactions on Evolutionary Computation 26.6. Oct. 2022. DOI

[142]

K. Röck • D. Rügamer • B. Bischl • U. von Toussaint • C. Rea • A. Maris • R. Granetz • C. G. Albert
Data augmentation for disruption prediction via robust surrogate models.
Journal of Plasma Physics 88.5. Oct. 2022. DOI

[141]

D. Rügamer • A. Bender • S. Wiegrebe • D. Racek • B. Bischl • C. L. Müller • C. Stachl
Factorized Structured Regression for Large-Scale Varying Coefficient Models.
ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

[140]

L. Bothmann • S. Strickroth • G. Casalicchio • D. Rügamer • M. Lindauer • F. Scheipl • B. Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science.
Teaching Machine Learning and Artificial Intelligence Workshop @ECML-PKDD 2022 - 3rd Teaching Machine Learning and Artificial Intelligence Workshop at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. URL

[139]

D. Deng • F. Karl • F. Hutter • B. Bischl • M. Lindauer
Efficient Automated Deep Learning for Time Series Forecasting.
Workshops @ECML-PKDD 2022 - Workshops at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

[138]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs.
MAD @MICCAI 2022 - 1st Workshop on Medical Applications with Disentanglements at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention. Singapore, Sep 18-22, 2022. DOI

[137]

R. Sonabend • A. Bender • S. Vollmer
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.
Bioinformatics 38.17. Sep. 2022. DOI GitHub

[136]

C. Fritz • M. Mehrl • P. W. Thurner • G. Kauermann
All that Glitters is not Gold: Relational Events Models with Spurious Events.
Network Science 11.2. Sep. 2022. DOI

[135]

W. Ghada • E. Casellas • J. Herbinger • A. Garcia-Benadí • L. Bothmann • N. Estrella • J. Bech • A. Menzel
Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar.
Remote Sensing 14.18. Sep. 2022. DOI

[134]

E. Dorigatti • B. Bischl • B. Schubert
Improved proteasomal cleavage prediction with positive-unlabeled learning.
Preprint (Sep. 2022). arXiv

[133]

E. Dorigatti • J. Schweisthal • B. Bischl • M. Rezaei
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision.
Preprint (Sep. 2022). arXiv GitHub

[132]

C. A. Scholbeck • H. Funk • G. Casalicchio
Algorithm-Agnostic Interpretations for Clustering.
Preprint (Sep. 2022). arXiv

[131]

S.-F. Zheng • J. Nam • E. Dorigatti • B. Bischl • S. Azizi • M. Rezaei
Joint Debiased Representation and Image Clustering Learning with Self-Supervision.
Preprint (Sep. 2022). arXiv GitHub

[130]

F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Representation Learning for Tablet and Paper Domain Adaptation in favor of Online Handwriting Recognition.
MPRSS @ICPR 2022 - 7th International Workshop on Multimodal pattern recognition of social signals in human computer interaction at the 26th International Conference on Pattern Recognition. Montreal, Canada, Aug 21-25, 2022. arXiv

[129]

M. van Smeden • G. Heinze • B. Van Calster • F. W. Asselbergs • P. E. Vardas • N. Bruining • P. de Jaegere • J. H. Moore • S. Denaxas • A.-L. Boulesteix • K. G. M. Moons
Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.
European Heart Journal 43.31. Aug. 2022. DOI

[128]

M. Schneble • G. Kauermann
Estimation of Latent Network Flows in Bike-Sharing Systems.
Statistical Modelling 22.2. Aug. 2022. DOI

[127]

C. Fritz • G. De Nicola • M. Rave • M. Weigert • Y. Khazaei • U. Berger • H. Küchenhoff • G. Kauermann
Statistical modelling of COVID-19 data: Putting generalized additive models to work.
Statistical Modelling 24.4. Aug. 2022. DOI

[126]

F. Ott • N. L. Raichur • D. Rügamer • T. Feigl • H. Neumann • B. Bischl • C. Mutschler
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression.
Preprint (Aug. 2022). arXiv

[125]

L. Schneider • L. Schäpermeier • R. Prager • B. Bischl • H. Trautmann • P. Kerschke
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
Preprint (Aug. 2022). arXiv

[124]

C. Fritz
Statistical approaches to dynamic networks in society.
Dissertation LMU München. Jul. 2022. DOI

[123]

F. Pfisterer • L. Schneider • J. Moosbauer • M. Binder • B. Bischl
YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization.
AutoML 2022 - International Conference on Automated Machine Learning. Baltimore, MD, USA, Jul 25-27, 2022. URL GitHub

[122]

L. Schneider • F. Pfisterer • P. Kent • J. Branke • B. Bischl • J. Thomas
Tackling neural architecture search with quality diversity optimization.
AutoML 2022 - International Conference on Automated Machine Learning. Baltimore, MD, USA, Jul 25-27, 2022. URL

[121]

A. Klaß • S. M. Lorenz • M. W. Lauer-Schmaltz • D. Rügamer • B. Bischl • C. Mutschler • F. Ott
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift.
STRL 2022 @IJCAI-ECAI 2022 - Workshop on Spatio-Temporal Reasoning and Learningat the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. URL

[120]

A. Khakzar • Y. Li • Y. Zhang • M. Sanisoglu • S. T. Kim • M. Rezaei • B. Bischl • N. Navab
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models.
IMLH @ICML 2022 - 2nd Workshop on Interpretable Machine Learning in Healthcare at the 39th International Conference on Machine Learning. Baltimore, MD, USA, Jul 17-23, 2022. arXiv

[119]

S. Dandl • F. Pfisterer • B. Bischl
Multi-Objective Counterfactual Fairness.
GECCO 2022 - Genetic and Evolutionary Computation Conference. Boston, MA, USA, Jul 09-13, 2022. DOI

[118]

L. Schneider • F. Pfisterer • J. Thomas • B. Bischl
A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning Models.
GECCO 2022 - Genetic and Evolutionary Computation Conference. Boston, MA, USA, Jul 09-13, 2022. DOI

[117]

M. Mittermeier • M. Weigert • D. Rügamer • H. Küchenhoff • R. Ludwig
A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble.
Environmental Research Letters 17.8. Jul. 2022. DOI

[116]

M. Schneble • G. Kauermann
Intensity Estimation on Geometric Networks with Penalized Splines.
Annals of Applied Statistics 16.2. Jun. 2022. DOI

[115]

Q. Au • J. Herbinger • C. Stachl • B. Bischl • G. Casalicchio
Grouped Feature Importance and Combined Features Effect Plot.
Data Mining and Knowledge Discovery 36. Jun. 2022. DOI

[114]

S. Kevork • G. Kauermann
Bipartite Exponential Random Graph Models with Nodal Random Effects.
Social Networks 70. Jun. 2022. DOI

[113]

P. Kopper • S. Wiegrebe • B. Bischl • A. Bender • D. Rügamer
DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis.
PAKDD 2022 - 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Chengdu, China, May 16-19, 2022. DOI

[112]

T. Ullmann • C. Hennig • A.-L. Boulesteix
Validation of cluster analysis results on validation data: A systematic framework.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12.3. May. 2022. DOI

[111]

D. Rügamer
Additive Higher-Order Factorization Machines.
Preprint (May. 2022). arXiv

[110]

J. Herbinger • B. Bischl • G. Casalicchio
REPID: Regional Effect Plots with implicit Interaction Detection.
AISTATS 2022 - 25th International Conference on Artificial Intelligence and Statistics. Virtual, Mar 28-30, 2022. URL

[109]

F. Pargent • F. Pfisterer • J. Thomas • B. Bischl
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features.
Computational Statistics 37. Mar. 2022. DOI

[108]

D. Strieder • M. Drton
On the choice of the splitting ratio for the split likelihood ratio test.
Electronic Journal of Statistics 16.2. Mar. 2022. DOI

[107]

C. Fritz • E. Dorigatti • D. Rügamer
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
Scientific Reports 12.3930. Mar. 2022. DOI

[106]

C. Sauer • M. Herrmann • C. Wiedemann • G. Casalicchio • A.-L. Boulesteix
Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12.2. Mar. 2022. DOI

[105]

F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Cross-Modal Common Representation Learning with Triplet Loss Functions.
Preprint (Mar. 2022). DOI

[104]

M. Rezaei • J. J. Näppi • B. Bischl • H. Yoshida
Bayesian uncertainty estimation for detection of long-tail and unseen conditions in abdominal images.
SPIE 2022 - SPIE Medical Imaging: Computer-Aided Diagnosis. San Diego, CA, USA, Feb 20-Mar 28, 2022. DOI

[103]

M. Rezaei • J. J. Näppi • B. Bischl • H. Yoshida
Deep mutual GANs: representation learning from multiple experts.
SPIE 2022 - SPIE Medical Imaging: Imaging Informatics for Healthcare, Research, and Applications. San Diego, CA, USA, Feb 20-Mar 28, 2022. DOI

[102]

G. De Nicola • B. Sischka • G. Kauermann
Mixture Models and Networks: The Stochastic Block Model.
Statistical Modelling 22.1-2. Feb. 2022. DOI

[101]

F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Joint Classification and Trajectory Regression of Online Handwriting Using a Multi-Task Learning Approach.
WACV 2022 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2022. DOI

[100]

J. Goldsmith • F. Scheipl
tf: S3 classes and methods for tidy functional data. R package.
2022. GitHub

[99]

J. Goldsmith • F. Scheipl
tidyfun: Clean, wholesome, tidy fun with functional data in R. R package.
2022. GitHub

[98]

W. Hartl • P. Kopper • A. Bender • F. Scheipl • A. G. Day • G. Elke • H. Küchenhoff
Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models.
Critical Care 26.7. Jan. 2022. DOI

[97]

C. Fritz • G. Kauermann
On the Interplay of Regional Mobility, Social Connectedness, and the Spread of COVID-19 in Germany.
Journal of the Royal Statistical Society. Series A (Statistics in Society) 185.1. Jan. 2022. DOI

[96]

A. Python • A. Bender • M. Blangiardo • J. B. Illian • Y. Lin • B. Liu • T. C. D. Lucas • S. Tan • Y. Wen • D. Svanidze • J. Yin
A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales.
Journal of the Royal Statistical Society. Series A (Statistics in Society) 185.1. Jan. 2022. DOI

[95]

E. Dorigatti • J. Goschenhofer • B. Schubert • M. Rezaei • B. Bischl
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection.
Preprint (Jan. 2022). arXiv

[94]

T. Weber • M. Ingrisch • M. Fabritius • B. Bischl • D. Rügamer
Survival-oriented embeddings for improving accessibility to complex data structures.
Bridging the Gap: from ML Research to Clinical Practice @NeurIPS 2021 - Workshop on Bridging the Gap: from Machine Learning Research to Clinical Practice at the 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. arXiv

[93]

T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Towards modelling hazard factors in unstructured data spaces using gradient-based latent interpolation.
Deep Generative Models and Downstream Applications @NeurIPS 2021 - Workshop on Deep Generative Models and Downstream Applications at the 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. PDF

[92]

J. Moosbauer • J. Herbinger • G. Casalicchio • M. Lindauer • B. Bischl
Explaining Hyperparameter Optimization via Partial Dependence Plots.
NeurIPS 2021 - 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. URL GitHub

[91]

Y. Zhang • A. Khakzar • Y. Li • A. Farshad • S. T. Kim • N. Navab
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information.
NeurIPS 2021 - Track on Datasets and Benchmarks at the 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. URL

[90]

M. Mittermeier • M. Weigert • D. Rügamer
Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach.
Tackling Climate Change with ML @NeurIPS 2021 - Workshop on Tackling Climate Change with Machine Learning at the 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. PDF

[89]

B. Bischl • G. Casalicchio • M. Feurer • P. Gijsbers • F. Hutter • M. Lang • R. G. Mantovani • J. N. van Rijn • J. Vanschoren
OpenML Benchmarking Suites.
Track on Datasets and Benchmarks @NeurIPS 2021 - Track on Datasets and Benchmarks at the 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. URL

[88]

S. Kevork • G. Kauermann
Iterative Estimation of Mixed Exponential Random Graph Models with Nodal Random Effects.
Network Science 9.4. Dec. 2021. DOI

[87]

C. Fritz • M. Mehrl • P. W. Thurner • G. Kauermann
The Role of Governmental Weapons Procurements in Forecasting Monthly Fatalities in Intrastate Conflicts: A Semiparametric Hierarchical Hurdle Model.
International Interactions 48.4. Nov. 2021. DOI

[86]

S. Hilbert • S. Coors • E. Kraus • B. Bischl • A. Lindl • M. Frei • J. Wild • S. Krauss • D. Goretzko • C. Stachl
Machine learning for the educational sciences.
Review of Education 9.3. Nov. 2021. DOI

[85]

M. Herrmann • F. Scheipl
A Geometric Perspective on Functional Outlier Detection.
Stats 4.4. Nov. 2021. DOI

[84]

A. Khakzar • Y. Zhang • W. Mansour • Y. Cai • Y. Li • Y. Zhang • S. T. Kim • N. Navab
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features.
MICCAI 2021 - 24th International Conference on Medical Image Computing and Computer Assisted Intervention. Strasbourg, France, Sep 27-Oct 01, 2021. DOI GitHub

[83]

S. Coors • D. Schalk • B. Bischl • D. Rügamer
Automatic Componentwise Boosting: An Interpretable AutoML System.
ADS @ECML-PKDD 2021 - Automating Data Science Workshop at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Virtual, Sep 13-17, 2021. arXiv

[82]

P. F. M. Baumann • T. Hothorn • D. Rügamer
Deep Conditional Transformation Models.
ECML-PKDD 2021 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Virtual, Sep 13-17, 2021. DOI

[81]

R. Sonabend • F. J. Király • A. Bender • B. Bischl • M. Lang
mlr3proba: An R Package for Machine Learning in Survival Analysis.
Bioinformatics 37.17. Sep. 2021. DOI

[80]

C. Fritz • P. W. Thurner • G. Kauermann
Separable and Semiparametric Network-based Counting Processes applied to the International Combat Aircraft Trades.
Network Science 9.3. Sep. 2021. DOI

[79]

F. Soleymani • M. Eslami • T. Elze • B. Bischl • M. Rezaei
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images.
Preprint (Sep. 2021). arXiv GitHub

[78]

M. P. Fabritius • M. Seidensticker • J. Rueckel • C. Heinze • M. Pech • K. J. Paprottka • P. M. Paprottka • J. Topalis • A. Bender • J. Ricke • A. Mittermeier • M. Ingrisch
Bi-Centric Independent Validation of Outcome Prediction after Radioembolization of Primary and Secondary Liver Cancer.
Journal of Clinical Medicine 10.16. Aug. 2021. DOI

[77]

H. Seibold • A. Charlton • A.-L. Boulesteix • S. Hoffmann
Statisticians, Roll Up Your Sleeves! There's A Crisis to be Solved.
Significance 18.4. Aug. 2021. DOI

[76]

F. Pfisterer • C. Kern • S. Dandl • M. Sun • M. P. Kim • B. Bischl
mcboost: Multi-Calibration Boosting for R.
The Journal of Open Source Software 6.64. Aug. 2021. DOI

[75]

A. Bauer • F. Scheipl • H. Küchenhoff
Registration for Incomplete Non-Gaussian Functional Data.
Preprint (Aug. 2021). arXiv

[74]

G. König • T. Freiesleben • M. Grosse-Wentrup
A causal perspective on meaningful and robust algorithmic recourse.
Algorithmic Recourse @ICML 2021 - Workshop on Algorithmic Recourse at the 38th International Conference on Machine Learning. Virtual, Jul 18-24, 2021. URL

[73]

J. Moosbauer • J. Herbinger • G. Casalicchio • M. Lindauer • B. Bischl
Towards Explaining Hyperparameter Optimization via Partial Dependence Plots.
AutoML @ICML 2021 - 8th Workshop on Automated Machine Learning at the 38th International Conference on Machine Learning. Virtual, Jul 18-24, 2021. URL

[72]

P. Gijsbers • F. Pfisterer • J. N. van Rijn • B. Bischl • J. Vanschoren
Meta-Learning for Symbolic Hyperparameter Defaults.
GECCO 2021 - Genetic and Evolutionary Computation Conference. Lile, France, Jul 10-14, 2021. DOI

[71]

F. Pfisterer • J. N. van Rijn • P. Probst • A. C. Müller • B. Bischl
Learning Multiple Defaults for Machine Learning Algorithms.
GECCO 2021 - Genetic and Evolutionary Computation Conference. Lile, France, Jul 10-14, 2021. DOI

[70]

A. Python • A. Bender • A. K. Nandi • P. A. Hancock • R. Arambepola • J. Brandsch • T. C. D. Lucas
Predicting non-state terrorism worldwide.
Science Advances 7.31. Jul. 2021. DOI

[69]

M. Binder • F. Pfisterer • M. Lang • L. Schneider • L. Kotthoff • B. Bischl
mlr3pipelines - Flexible Machine Learning Pipelines in R.
Journal of Machine Learning Research 22.184. Jun. 2021. URL

[68]

H. Seibold • S. Czerny • S. Decke • R. Dieterle • T. Eder • S. Fohr • N. Hahn • R. Hartmann • C. Heindl • P. Kopper • D. Lepke • V. Loidl • M. M. Mandl • S. Musiol • J. Peter • A. Piehler • E. Rojas • S. Schmid • H. Schmidt • M. Schmoll • L. Schneider • X.-Y. To • V. Tran • A. Völker • M. Wagner • J. Wagner • M. Waize • H. Wecker • R. Yang • S. Zellner • M. Nalenz
A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses.
PLOS One 16.6. Jun. 2021. DOI

[67]

G. König • T. Freiesleben • B. Bischl • G. Casalicchio • M. Grosse-Wentrup
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT).
Preprint (Jun. 2021). arXiv

[66]

I. Gerostathopoulos • F. Plášil • C. Prehofer • J. Thomas • B. Bischl
Automated Online Experiment-Driven Adaptation--Mechanics and Cost Aspects.
IEEE Access 9. Apr. 2021. DOI

[65]

P. Kopper • S. Pölsterl • C. Wachinger • B. Bischl • A. Bender • D. Rügamer
Semi-Structured Deep Piecewise Exponential Models.
AAAI-SPACA 2021 - AAAI Spring Symposium Series on Survival Prediction: Algorithms, Challenges and Applications. Palo Alto, California, USA, Mar 21-24, 2021. PDF

[64]

S. Klau • S. Hoffmann • C. J. Patel • J. P. A. Ioannidis • A.-L. Boulesteix
Examining the robustness of observational associations to model, measurement and sampling uncertainty with the vibration of effects framework.
International Journal of Epidemiology 50.1. Feb. 2021. DOI

[63]

J. Goschenhofer • R. Hvingelby • D. Rügamer • J. Thomas • M. Wagner • B. Bischl
Deep Semi-Supervised Learning for Time Series Classification.
Preprint (Feb. 2021). arXiv

[62]

G. König • C. Molnar • B. Bischl • M. Grosse-Wentrup
Relative Feature Importance.
ICPR 2020 - 25th International Conference on Pattern Recognition. Virtual - Milano, Italy, Jan 10-15, 2021. DOI

[61]

M. Becker • S. Gruber • J. Richter • J. Moosbauer • B. Bischl
mlr3hyperband: Hyperband for 'mlr3'.
2021. URL GitHub

[60]

M. Becker • M. Lang • J. Richter • B. Bischl • D. Schalk
mlr3tuning: Tuning for 'mlr3'.
2021. URL GitHub

[59]

M. Becker • J. Richter • M. Lang • B. Bischl • M. Binder
bbotk: Black-Box Optimization Toolkit.
2021. URL GitHub

[58]

M. Binder
mlrintermbo: Model-Based Optimization for 'mlr3' through 'mlrMBO'.
2021. URL GitHub

[57]

M. Lang
mlr3measures: Performance Measures for 'mlr3'.
2021. URL

[56]

M. Lang • B. Bischl • J. Richter • X. Sun • M. Binder
paradox: Define and Work with Parameter Spaces for Complex Algorithms.
2021. URL GitHub

[55]

D. Rügamer • F. Pfisterer • P. Baumann
deepregression: Fitting Semi-Structured Deep Distributional Regression in R.
2021. URL

[54]

P. Schratz • M. Becker
mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'.
2021. URL

[53]

M. Herrmann • F. Scheipl
Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction.
Preprint (Dec. 2020). arXiv

[52]

A. Agrawal • F. Pfisterer • B. Bischl • F. Buet-Golfouse • S. Sood • J. Chen • S. Shah • S. Vollmer
Debiasing classifiers: is reality at variance with expectation?
Preprint (Nov. 2020). arXiv

[51]

V. Melnychuk • E. Faerman • I. Manakov • T. Seidl
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels.
Workshop @CIKM 2020 - Workshop at the 29th ACM International Conference on Information and Knowledge Management. Galway, Ireland, Oct 19-23, 2020. PDF GitHub

[50]

A.-L. Boulesteix • S. Hoffmann • A. Charlton • H. Seibold
A replication crisis in methodological research?
Significance 17.5. Oct. 2020. DOI

[49]

D. Rügamer • F. Pfisterer • B. Bischl
Neural Mixture Distributional Regression.
Preprint (Oct. 2020). arXiv

[48]

A. Bender • D. Rügamer • F. Scheipl • B. Bischl
A General Machine Learning Framework for Survival Analysis.
ECML-PKDD 2020 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Virtual, Sep 14-18, 2020. DOI

[47]

C. Molnar • G. Casalicchio • B. Bischl
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges.
Workshops @ECML-PKDD 2020 - Workshops at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Virtual, Sep 14-18, 2020. DOI

[46]

S. Dandl • C. Molnar • M. Binder • B. Bischl
Multi-Objective Counterfactual Explanations.
PPSN 2020 - 16th International Conference on Parallel Problem Solving from Nature. Leiden, Netherlands, Sep 05-09, 2020. DOI

[45]

M. Herrmann • P. Probst • R. Hornung • V. Jurinovic • A.-L. Boulesteix
Large-scale benchmark study of survival prediction methods using multi-omics data.
Briefings in Bioinformatics. Aug. 2020. DOI

[44]

C. Fritz • M. Lebacher • G. Kauermann
Tempus volat, hora fugit: A survey of tie-oriented dynamic network models in discrete and continuous time.
Statistica Neerlandica 74.3. Aug. 2020. DOI

[43]

M. Binder • F. Pfisterer • B. Bischl
Collecting empirical data about hyperparameters for data driven AutoML.
AutoML @ICML 2020 - 7th Workshop on Automated Machine Learning at the 37th International Conference on Machine Learning. Virtual, Jul 18, 2020. PDF

[42]

C. Molnar • G. König • J. Herbinger • T. Freiesleben • S. Dandl • C. A. Scholbeck • G. Casalicchio • M. Grosse-Wentrup • B. Bischl
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
XXAI @ICML 2020 - Workshop on Extending Explainable AI Beyond Deep Models and Classifiers at the 37th International Conference on Machine Learning. Virtual, Jul 12-18, 2020. DOI

[41]

M. Binder • J. Moosbauer • J. Thomas • B. Bischl
Multi-Objective Hyperparameter Tuning and Feature Selection Using Filter Ensembles.
GECCO 2020 - Genetic and Evolutionary Computation Conference. Cancun, Mexico, Jul 08-12, 2020. DOI

[40]

N. Ellenbach • A.-L. Boulesteix • B. Bischl • K. Unger • R. Hornung
Improved outcome prediction across data sources through robust parameter tuning.
Journal of Classification 38. Jul. 2020. DOI

[39]

C. Stachl • Q. Au • R. Schoedel • S. D. Gosling • G. M. Harari • D. Buschek • S. T. Völkel • T. Schuwerk • M. Oldemeier • T. Ullmann • H. Hussmann • B. Bischl • M. Bühner
Predicting personality from patterns of behavior collected with smartphones.
Proceedings of the National Academy of Sciences 117.30. Jul. 2020. DOI

[38]

A. Beyer • G. Kauermann • H. Schütze
Embedding Space Correlation as a Measure of Domain Similarity.
LREC 2020 - 12th International Conference on Language Resources and Evaluation. Marseille, France, May 13-15, 2020. URL

[37]

S. Klau • M.-L. Martin-Magniette • A.-L. Boulesteix • S. Hoffmann
Sampling uncertainty versus method uncertainty: a general framework with applications to omics biomarker selection.
Biometrical Journal 62.3. May. 2020. DOI

[36]

M. Berrendorf • E. Faerman • V. Melnychuk • V. Tresp • T. Seidl
Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned.
ECIR 2020 - 42nd European Conference on Information Retrieval. Virtual, Apr 14-17, 2020. DOI GitHub

[35]

M. Becker • P. Schratz • M. Lang • B. Bischl
mlr3fselect: Feature Selection for 'mlr3'.
2020. URL

[34]

M. Binder • F. Pfisterer • L. Schneider • B. Bischl • M. Lang • S. Dandl
mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'.
2020. URL GitHub

[33]

M. Herrmann
fda-ndr: Unsupervised Functional Data Analysis via Nonlinear Dimension Reduction. R package.
2020. GitHub

[32]

M. Herrmann
manifun: Collection of functions to work with embeddings and functional data. R package.
2020. GitHub

[31]

M. Lang
mlr3db: Data Base Backend for 'mlr3'.
2020. URL GitHub

[30]

M. Lang
mlr3oml: Connector Between 'mlr3' and 'OpenML'.
2020. URL GitHub

[29]

M. Lang • Q. Au • S. Coors • P. Schratz
mlr3learners: Recommended Learners for 'mlr3'.
2020. URL GitHub

[28]

M. Lang • P. Schratz • R. Sonabend
mlr3viz: Visualizations for 'mlr3'.
2020. URL GitHub

[27]

D. Pulatov • M. Lang
mlr3cluster: Cluster Extension for 'mlr3'.
2020. URL GitHub

[26]

F. Scheipl • J. Goldsmith • J. Wrobel
tidyfun: Tools for Tidy Functional Data. R package.
2020. URL GitHub

[25]

P. Schratz • M. Lang • B. Bischl • M. Binder
mlr3filters: Filter Based Feature Selection for 'mlr3'.
2020. URL GitHub

[24]

R. Sonabend • F. J. Kiraly • A. Bender • B. Bischl • M. Lang
mlr3proba: Probabilistic Supervised Learning for 'mlr3'. R package version 0.2.6.
2020. DOI URL

[23]

J. Wrobel • A. Bauer • J. McDonnel • F. Scheipl
registr: Curve Registration for Exponential Family Functional Data. R package.
2020. GitHub

[22]

M. Urban • K. Heckel • C. Berger • P. Schratz • I. P. Smit • T. Strydom • J. Baade • C. Schmullius
Woody cover mapping in the savanna ecosystem of the Kruger National Park using Sentinel-1 C-Band time series data.
Koedoe 62.1. Jan. 2020. DOI

[21]

D. Davletshina • V. Melnychuk • V. Tran • H. Singla • M. Berrendorf • E. Faerman • M. Fromm • M. Schubert
Unsupervised Anomaly Detection for X-Ray Images.
Preprint (Jan. 2020). arXiv GitHub

[20]

M. Lang • M. Binder • J. Richter • P. Schratz • F. Pfisterer • S. Coors • Q. Au • G. Casalicchio • L. Kotthoff • B. Bischl
mlr3: A modern object-oriented machine learning framework in R.
The Journal of Open Source Software 4.44. Dec. 2019. DOI

[19]

M. Binder • J. Moosbauer • J. Thomas • B. Bischl
Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles.
Preprint (Dec. 2019). arXiv

[18]

F. Pfisterer • L. Beggel • X. Sun • F. Scheipl • B. Bischl
Benchmarking time series classification -- Functional data vs machine learning approaches.
Preprint (Nov. 2019). arXiv

[17]

F. Pfisterer • J. Thomas • B. Bischl
Towards Human Centered AutoML.
Preprint (Nov. 2019). arXiv

[16]

G. König • M. Grosse-Wentrup
A Causal Perspective on Challenges for AI in Precision Medicine.
PMBC 2019 - 2nd International Congress on Precision Medicine. Munich, Germany, Oct 14-15, 2019.

[15]

L. Beggel • M. Pfeiffer • B. Bischl
Robust Anomaly Detection in Images Using Adversarial Autoencoders.
ECML-PKDD 2019 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Wuerzburg, Germany, Sep 16-20, 2019. DOI

[14]

J. Goschenhofer • F. M. J. Pfister • K. A. Yuksel • B. Bischl • U. Fietzek • J. Thomas
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning.
ECML-PKDD 2019 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Wuerzburg, Germany, Sep 16-20, 2019. DOI

[13]

C. Molnar • G. Casalicchio • B. Bischl
Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability.
ECML-PKDD 2019 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Wuerzburg, Germany, Sep 16-20, 2019. DOI

[12]

C. A. Scholbeck • C. Molnar • C. Heumann • B. Bischl • G. Casalicchio
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model Agnostic Interpretations.
ECML-PKDD 2019 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Wuerzburg, Germany, Sep 16-20, 2019. DOI

[11]

F. Pfisterer • S. Coors • J. Thomas • B. Bischl
Multi-Objective Automatic Machine Learning with AutoxgboostMC.
Workshops @ECML-PKDD 2019 - Workshops at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Wuerzburg, Germany, Sep 16-20, 2019. arXiv

[10]

L. M. Weber • W. Saelens • R. Cannoodt • C. Soneson • A. Hapfelmeier • P. P. Gardner • A.-L. Boulesteix • Y. Saeys • M. D. Robinson
Essential guidelines for computational method benchmarking.
Genome Biology 20.125. Jun. 2019. DOI

[9]

J. Thomas
Gradient boosting in automatic machine learning: feature selection and hyperparameter optimization.
Dissertation LMU München. Apr. 2019. DOI

[8]

Q. Au • D. Schalk • G. Casalicchio • R. Schoedel • C. Stachl • B. Bischl
Component-Wise Boosting of Targets for Multi-Output Prediction.
Preprint (Apr. 2019). arXiv

[7]

G. Casalicchio
On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models.
Dissertation LMU München. Mar. 2019. DOI

[6]

P. Probst • A.-L. Boulesteix • B. Bischl
Tunability: Importance of Hyperparameters of Machine Learning Algorithms.
Journal of Machine Learning Research 20. Mar. 2019. PDF

[5]

C. Happ • F. Scheipl • A.-A. Gabriel • S. Greven
A general framework for multivariate functional principal component analysis of amplitude and phase variation.
Stat 8.2. Feb. 2019. DOI

[4]

M. Binder • S. Dandl • J. Moosbauer
mosmafs: Multi-Objective Simultaneous Model and Feature Selection. R package.
2019. GitHub

[3]

J. Goldsmith • F. Scheipl • L. Huang • J. Wrobel • C. Di • J. Gellar • J. Harezlak • M. W. McLean • B. Swihart • L. Xiao • C. Crainiceanu • P. T. Reiss
refund: Regression with Functional Data.
2019. URL

[2]

P. Probst • M. N. Wright • A.-L. Boulesteix
Hyperparameters and Tuning Strategies for Random Forest.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9.3. Jan. 2019. DOI

[1]

J. Minkwitz • F. Scheipl • E. Binder • C. Sander • U. Hegerl • H. Himmerich
Generalised functional additive models for brain arousal state dynamics.
IPEG 2018 - 20th International Pharmaco-EEG Society for Preclinical and Clinical Electrophysiological Brain Research Meeting. Zurich, Switzerland, Nov 21-25, 2018. DOI

A2 | Mathematical Foundations

Some of the tremendous successes of ML have been achieved through the use of mathematical insights. The contribution of our mathematicians in MCML can be divided into two main research areas: Mathematics for ML, i.e. mathematical principles are used to develop new reliable ML algorithms, and ML for mathematics, i.e. ML is used to advance mathematical research, e.g. in imaging, inverse problems, optimal control, or numerical analysis of partial differential equations.

Ulrich Bauer

Prof. Dr.

Core PI

Applied Topology and Geometry

Felix Dietrich

Prof. Dr.

Collaborating PI

Physics-enhanced Machine Learning

Massimo Fornasier

Prof. Dr.

Core PI

Applied Numerical Analysis

Reinhard Heckel

Prof. Dr.

Core PI

Machine Learning and Information Processing

Christian Kühn

Prof. Dr.

Collaborating PI

Multiscale and Stochastic Dynamics

Gitta Kutyniok

Prof. Dr.

Core PI

Mathematical Foundations of Artificial Intelligence

Johannes Maly

Prof. Dr.

Collaborating PI

Mathematical Data Science and Artificial Intelligence

Holger Rauhut

Prof. Dr.

Core PI

Mathematical Data Science and Artificial Intelligence

Suvrit Sra

Prof. Dr.

Core PI

Resource Aware Machine Learning

Tom Sterkenburg

Dr.

Associated JRG Leader Epistemology in ML

Epistemological Foundations of Machine Learning

©all images: LMU | TUM

Publications in Research Area A2

[225]

C. Bülte • Y. Sale • G. Kutyniok • E. Hüllermeier
Uncertainty Quantification for Regression: A Unified Framework based on kernel scores.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[224]

C. Bülte • Y. Sale • T. Löhr • P. Hofman • G. Kutyniok • E. Hüllermeier
An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[223]

Y. Sale • C. Bülte • F. Czaja • J. Stiller • E. Hüllermeier
What Uncertainties Do We Need for Dynamical Systems?
EIML @ICML 2026 - Workshop on Epistemic Intelligence in Machine Learning at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. URL

[222]

F. Eichin • Y. Du • P. Mondorf • M. Matveev • B. Plank • M. A. Hedderich
ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[221]

A. Evangelidis • F. Krahmer
Width Independent Bounds for the Local Lipschitz Constant of Deep Neural Networks at Random Initialization and after Lazy Training.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[220]

L. Galli • C. Fox • W. Bartolomaeus • M. Schmidt • H. Rauhut
Flatland: The Adventures of Gradient Descent with Large Step Sizes.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[219]

M. Matveev • V. Fojtik • H.-H. Chou • G. Kutyniok • J. Maly
Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[218]

S. N. Ramachandran • S. Sra
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[217]

V. Stein • J. M. de Frutos
Approximating f -Divergences with Rank Statistics.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[216]

V. Stein • J. M. de Frutos
Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[215]

H. Andrade-Loarca • J. Hege • D. Cremers • G. Kutyniok
Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point Clouds.
3D4S @CVPR 2026 - Workshop on 3D Geometry Generation for Scientific Computing at the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Denver, CO, USA, Jun 03-07, 2026. To be published. Preprint available. URL

[214]

G. Eskandar • F. Shen • M. Altillawi • D. Chen • Y. Bai • L. Yang • Z. Liu
VideoWeaver: Multimodal Multi-View Video-to-Video Transfer for Embodied Agents.
CVPR 2026 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Denver, CO, USA, Jun 03-07, 2026. To be published. Preprint available. arXiv

[213]

X. Sun • A. Jordana • M. Fornasier • J. Etesami • M. Khadiv
Consensus-based Optimization (CBO) for trajectory optimization in Robotics.
FOR @ICRA 2026 - 2nd Workshop on Frontiers of Optimization for Robotics at the IEEE International Conference on Robotics and Automation. Vienna, Austria, Jun 01-05, 2026. URL

[212]

Y. Bai • L. Yang • G. Eskandar • F. Shen • M. Altillawi • Z. Liu • G. Kutyniok
DRAW2ACT: Turning Depth-Encoded Trajectories into Robotic Demonstration Videos.
ICRA 2026 - IEEE International Conference on Robotics and Automation. Vienna, Austria, Jun 01-05, 2026. To be published. Preprint available. arXiv

[211]

L. Yang • Y. Bai • G. Eskandar • F. Shen • M. Altillawi • D. Chen • Z. Liu • A. Valada
CoVAR: Co-generation of Video and Action for Robotic Manipulation via Multi-Modal Diffusion.
ICRA 2026 - IEEE International Conference on Robotics and Automation. Vienna, Austria, Jun 01-05, 2026. To be published. Preprint available. arXiv

[210]

L. Yang • Y. Bai • Y. Wang • I. Alsarraj • G. Kutyniok • Z. Wang • K. Wu
Lightweight Learning from Actuation-Space Demonstrations via Flow Matching for Whole-Body Soft Robotic Grasping.
IEEE Robotics and Automation Letters 11.6. Jun. 2026. DOI

[209]

Y. Bai • G. Eskandar • Z. Liu • G. Kutyniok
Physics-Informed Video Diffusion for Shallow Water Equations.
ICASSP 2026 - IEEE International Conference on Acoustics, Speech and Signal Processing. Barcelona, Spain, May 04-08, 2026. DOI

[208]

E. M. Achour • K. Kohn • H. Rauhut
The Riemannian Geometry associated to Gradient Flows of Linear Convolutional Networks.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. Preprint available. arXiv

[207]

A. Scagliotti • F. Scagliotti • L. Locati • F. Sottotetti
Ensemble optimal control for managing drug resistance in cancer therapies.
Bulletin of Mathematical Biology 88.92. May. 2026. DOI

[206]

F. Colasanto • M. Focardi • M. Fornasier • F. Mattesini
Sharp Rates of MMD Empirical Estimation with Power Kernels.
Preprint (May. 2026). arXiv

[205]

A. Scagliotti • T. M. Surowiec
Risk-Averse Ensemble Control for Control-Affine Systems.
Preprint (May. 2026). arXiv

[204]

T. F. Sterkenburg
Statistical learning theory and Occam's razor: Regularization.
Preprint (May. 2026). URL

[203]

C. Datar • T. Kapoor • A. Chandra • Q. Sun • E. L. Bolager • I. Burak • A. Veselovska • M. Fornasier • F. Dietrich
Fast training of accurate physics-informed neural networks without gradient descent.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. Oral Presentation. To be published. Preprint available. arXiv

[202]

E. Araya • M. Datres • G. Kutyniok
Random Spiking Neural Networks are Stable and Spectrally Simple.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[201]

E. Guha • R. Marten • S. Keh • N. Raoof • G. Smyrnis • H. Bansal • M. Nezhurina • J. Mercat • T. Vu • Z. Sprague • A. Suvarna • B. Feuer • L. Chen • Z. Khan • E. Frankel • S. Grover • C. Choi • N. Muennighoff • S. Su • W. Zhao • J. Yang • S. Pimpalgaonkar • K. Sharma • C. C.-J. Ji • Y. Deng • S. Pratt • V. Ramanujan • J. Saad-Falcon • J. Li • A. Dave • A. Albalak • K. Arora • B. Wulfe • C. Hegde • G. Durrett • S. Oh • M. Bansal • S. Gabriel • A. Grover • K.-W. Chang • V. Shankar • A. Gokaslan • M. A. Merrill • T. Hashimoto • Y. Choi • J. Jitsev • R. Heckel • M. Sathiamoorthy • A. G. Dimakis • L. Schmidt
OpenThoughts: Data Recipes for Reasoning Models.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv URL

[200]

S. Maskey • R. Paolino • F. Jogl • G. Kutyniok • J. Lutzeyer
Graph Representational Learning: When Does More Expressivity Hurt Generalization?
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[199]

A. Rahma • C. Datar • A. Cukarska • F. Dietrich
Rapid training of Hamiltonian graph networks without gradient descent.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[198]

M. Seleznova • H.-H. Chou • C. M. Verdun • G. Kutyniok
GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[197]

J. von Berg • A. Fono • M. Datres • S. Maskey • G. Kutyniok
The Price of Robustness: Stable Classifiers Need Overparameterization.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[196]

K. Wang • T. Klug • S. Ruschke • J. Kirschke • R. Heckel
Reliable Evaluation of MRI Motion Correction: Dataset and Insights.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[195]

D. A. Nguyen • M. Datres • E. Araya • G. Kutyniok
Expressive Power of Recurrent Spiking Neural Networks for Sequence Modeling.
TSALM @ICLR 2026 - Workshop on Time Series in the Age of Large Models at the 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[194]

T. F. Sterkenburg
Values in machine learning: what follows from underdetermination?
AI and Ethics 6.258. Apr. 2026. DOI

[193]

J. Beddrich • E. Chenchene • M. Fornasier • H. Huang • B. Wohlmuth
Constrained consensus-based optimization and numerical heuristics for the few particle regime.
Journal of Global Optimization. Apr. 2026. DOI GitHub

[192]

U. Bauer • T. Brüstle • L. Scoccola
An Algebraic Introduction to Persistence.
Preprint (Apr. 2026). arXiv

[191]

E. L. Bolager • B. Hamzi • H. Owhadi • I. G. Kevrekidis • F. Dietrich
Dictionary learning for Kernel EDMD.
Preprint (Apr. 2026). arXiv

[190]

A. Fono • N. Wedlich • H. Boche • G. Kutyniok
Complexity Theory meets Ordinary Differential Equations.
Preprint (Apr. 2026). arXiv

[189]

F. Körner • M. Matveev • F. Eichin • G. Kutyniok • B. Plank • M. A. Hedderich
Copy First, Translate Later: Interpreting Translation Dynamics in Multilingual Pretraining.
Preprint (Apr. 2026). arXiv

[188]

C. Kühn • J. Yoon
Spectral Selection in Symmetric Self-Attention Dynamics.
Preprint (Apr. 2026). arXiv

[187]

J. Li • S. Huang • H. Feng • D.-X. Zhou • G. Kutyniok
Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension.
Preprint (Apr. 2026). arXiv

[186]

Z. Monfared • S. Malhotra • S. Hajime • I. Kevrekidis • F. Dietrich
On the algebra of Koopman eigenfunctions and on some of their infinities.
Preprint (Apr. 2026). arXiv

[185]

A. Fono • M. Singh • E. Araya • P. C. Petersen • H. Boche • G. Kutyniok
Mathematical Foundations of Spiking Neural Networks: Strengths, challenges, and computational paradigm potential [Special Issue on the Mathematics of deep Learning].
IEEE Signal Processing Magazine 43.2. Mar. 2026. DOI

[184]

U. Bauer • F. Lenzen • M. Lesnick
Dualities in Multiparameter Persistence.
Preprint (Mar. 2026). arXiv

[183]

T. Karvonen • G. Santin • T. Wenzel
Piecewise linear interpolation via kernels.
Preprint (Mar. 2026). arXiv

[182]

C. Kühn • S.-V. Kuntz • T. Wöhrer
Universal Approximation Constraints of Narrow ResNets: The Tunnel Effect.
Preprint (Mar. 2026). arXiv GitHub

[181]

T. F. Sterkenburg
Solomonoff induction.
Preprint (Mar. 2026). arXiv

[180]

K. Wang • R. Heckel
Test-time RL alignment exposes task familiarity artifacts in LLM benchmarks.
Preprint (Mar. 2026). arXiv

[179]

C. Kühn • S.-V. Kuntz
Analysis of the geometric structure of neural networks and neural ODEs via morse functions.
Advances in Computational Mathematics 52.9. Feb. 2026. DOI

[178]

N. Bhasker • F. R. Kolbinger • S. Hu • G. Kutyniok • S. Speidel
Adaptive-CaRe: Adaptive Causal Regularization for Robust Outcome Prediction.
Preprint (Feb. 2026). arXiv

[177]

M. Fornasier • H. Huang • J. Klemenc • G. Malaspina
From Consensus-Based Optimization to Evolution Strategies: Proof of Global Convergence.
Preprint (Feb. 2026). arXiv

[176]

V. Hoang • S. Krumscheid • H. Rauhut • R. Tempone
PurSAMERE: Reliable Adversarial Purification via Sharpness-Aware Minimization of Expected Reconstruction Error.
Preprint (Feb. 2026). arXiv

[175]

N. Leopold-Kerschbaumer • T. Halenke • S. Süzeroğlu • M. Jung • M. Seleznova • N. Thorisch • J. Lorenz • T. Bocklitz • B. M. Eskofier • G. Kutyniok • F. Krausz • K.
Conditional deep generative modeling of blood-based infrared spectra enables controlled in-silico phenotyping studies.
Preprint (Feb. 2026). DOI

[174]

J. Maly • K. Neuner • S. Vadia
Computing the SVD efficiently with photonic chips.
Preprint (Feb. 2026). arXiv

[173]

J. Maly • A. Veselovska
Reliable one-bit quantization of bandlimited graph data via single-shot noise shaping.
Preprint (Feb. 2026). arXiv

[172]

L. Paul • H. Rauhut • M. Burger • S. Kabri • T. Roith
Allure of Craquelure: A Variational-Generative Approach to Crack Detection in Paintings.
Preprint (Feb. 2026). arXiv

[171]

X. Sun • A. Jordana • M. Fornasier • J. Etesami • M. Khadiv
Consensus-based optimization (CBO): Towards Global Optimality in Robotics.
Preprint (Feb. 2026). arXiv

[170]

C. Fiedler
Statistical Learning Theory for Distributional Classification.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[169]

X. Jian • P. Zhang • L. Tian • F. Ji • W. Liang • W. P. Tay • B. Wen • F. Krahmer
Conformal Prediction for Multi-Source Detection on a Network.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[168]

A. Fono • G. Kutyniok • H. Boche
How to realize efficient Spiking Neural Networks?
MATH4AI @AAAI 2026 - Workshop on Foretell of Future AI from Mathematical Foundation at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. URL

[167]

C. Kneissl • C. Bülte • P. Scholl • G. Kutyniok
Improved probabilistic regression using diffusion models.
NLDL 2026 - Northern Lights Deep Learning Conference. Tromsø, Norway, Jan 06-08, 2026. To be published. Preprint available. URL

[166]

M. Fornasier • J. Klemenc • A. Scagliotti
Trade-off Invariance Principle for Minimizers of Regularized Functionals.
Journal of Optimization Theory and Applications 208.78. Jan. 2026. DOI

[165]

J.-M. Diederen • H. Rauhut • U. Terstiege
Convergence of gradient flow for learning convolutional neural networks.
Preprint (Jan. 2026). arXiv

[164]

D. S. Singh • L. Herrmann • T. Bürchner • F. Dietrich • S. Kollmannsberger
Graph Neural Networks for Full Waveform Inversion.
Preprint (Jan. 2026). URL

[163]

L. Sun
On the Concavity of Tsallis Entropy along the Heat Flow.
Preprint (Jan. 2026). arXiv

[162]

T. Wenzel
Sharp inverse statements for kernel approximation: Superconvergence and saturation.
Preprint (Jan. 2026). arXiv

[161]

T. Wenzel • G. Santin
On the optimal shape parameter for kernel methods: Sharp direct and inverse statements.
Preprint (Jan. 2026). arXiv

[160]

C. Kneissl • C. Bülte • P. Scholl • G. Kutyniok
Uncertainty-aware diffusion models for probabilistic regression.
EIML @EurIPS 2025 - Workshop on Epistemic Intelligence in Machine Learning at the European Conference on Information Processing Systems. Copenhagen, Denmark, Dec 03-05, 2025. URL

[159]

M. Kiener • J. Bozenhard • G. Kutyniok • S. Nyholm
The ethics of analog AI.
AI and Ethics 6.27. Dec. 2025. DOI

[158]

C. Geldhauser • M. Herrmann • D. Janßen
Traveling Phase Interfaces in Viscous Forward–Backward Diffusion Equations.
Journal of Dynamics and Differential Equations.4. Dec. 2025. DOI

[157]

S. Avesani • L. Ling • F. Marchetti • T. Wenzel
Sobolev Algorithm for Local Smoothness Analysis (SALSA) via Sharp Direct and Inverse Statements.
Preprint (Dec. 2025). arXiv

[156]

U. Bauer • T. K. Dey • M. Kerber • F. Russold • M. Söls
Fast free resolutions of bifiltered chain complexes.
Preprint (Dec. 2025). arXiv

[155]

J. Li • I. Rosellon-Inclan • G. Kutyniok • J.-L. Starck
CHEM: Estimating and Understanding Hallucinations in Deep Learning for Image Processing.
Preprint (Dec. 2025). arXiv

[154]

M. Mollenhauer • C. Fiedler
Fuk-Nagaev inequality in smooth Banach spaces: Optimum bounds for distributions of heavy-tailed martingales.
Preprint (Dec. 2025). arXiv

[153]

N. Bar • M. Seleznova • Y. Alexander • G. Kutyniok • R. Giryes
Revisiting Glorot Initialization for Long-Range Linear Recurrences.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[152]

G. König • H. Fokkema • T. Freiesleben • C. Mendler-Dünner • U. von Luxburg
Performative Validity of Recourse Explanations.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[151]

P.-F. Massiani • C. Fiedler • L. Haverbeck • F. Solowjow • S. Trimpe
Kernel conditional tests from learning-theoretic bounds.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[150]

S. N. Ramachandran • M. K. Lal • S. Sra
Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[149]

Y. Mansour • R. Heckel
Measuring Fingerprints of Web-filtered Text Datasets and Fingerprint Propagation Through Training.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Spotlight Presentation. URL

[148]

S. Bamberger • R. Heckel • F. Krahmer
Approximating Positive Homogeneous Functions with Scale Invariant Neural Networks.
Journal of Approximation Theory 311.106177. Nov. 2025. DOI

[147]

S. Abdulsalaam • M. Ali
Rank-sparsity decomposition for planted quasi clique recovery.
Journal of Global Optimization. Nov. 2025. DOI

[146]

C. Fiedler • A. Scagliotti
Towards optimal control of ensembles of discrete-time systems.
Preprint (Nov. 2025). arXiv

[145]

L. Sacchelli • A. Scagliotti
A case study in ensemble optimal control for Bayesian input design.
Preprint (Nov. 2025). arXiv

[144]

Z. Shumaylov • P. Zaika • P. Scholl • G. Kutyniok • L. Horesh • C.-B. Schönlieb
When is a System Discoverable from Data? Discovery Requires Chaos.
Preprint (Nov. 2025). arXiv

[143]

Y. Mansour • R. Heckel
GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration.
ASILOMAR 2025 - 59th Asilomar Conference on Signals, Systems, and Computers. Pacific Grove, CA, USA, Oct 26-29, 2025. DOI

[142]

S. Ullah • S. S. Sahoo • C. Li • C. Li • L. Liu • T. S. Pereira • B. Wen • X. Yin • A. Darjani • N. Kavand • C. Bodla • R. Y. Panduga • A. Holemadlu • J. Maly • J. Förste • S. Vadia • X. S. Hu • A. Kumar
Invited Paper: Circuit and Architecture Design with Emerging Computing Paradigms.
ICCAD 2025 - 44th IEEE/ACM International Conference on Computer-Aided Design. Munich, Germany, Oct 26-30, 2025. DOI

[141]

S. Kolek • A. Chattopadhyay • K. H. R. Chan • H. Andrade-Loarca • G. Kutyniok • R. Vidal
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit.
ICCV 2025 - IEEE/CVF International Conference on Computer Vision. Honolulu, Hawai’i, Oct 19-23, 2025. DOI

[140]

O. Åström • C. Geldhauser • M. Grillitsch • O. Hall • A. Sopasakis
Enhancing Carbon Emission Reduction Strategies using OCO and ICOS data.
Scientific Reports 15.36297. Oct. 2025. DOI

[139]

M. Fornasier • L. Sun • R. Ward
Large-Time Analysis of the Langevin Dynamics for Energies Fulfilling Polyak-Lojasiewicz Conditions.
Preprint (Oct. 2025). arXiv

[138]

T. Freiesleben • S. Zezulka
The Benchmarking Epistemology: Construct Validity for Evaluating Machine Learning Models.
Preprint (Oct. 2025). arXiv

[137]

R. Rouatbi • J.-E. Suarez Cardona • A. Villaronga-Luque • J. V. Veenvliet • I. F. Sbalzarini
A Continuous and Interpretable Morphometric for Robust Quantification of Dynamic Biological Shapes.
Preprint (Oct. 2025). arXiv

[136]

J. E. Suarez • H. Boche • G. Kutyniok
A Variational Framework for the Algorithmic Complexity of PDE Solutions.
Preprint (Oct. 2025). arXiv

[135]

C. Fiedler • S. Trimpe
On the Analysis of Suboptimal Nonlinear Model Predictive Control Schemes Without Terminal Constraints.
IEEE Control Systems Letters 9. Sep. 2025. DOI

[134]

A. A. Guth • S. Abdulsalaam • H. Rauhut • D. Heberling
Numerical Analysis of Mask-Based Phase Reconstruction in Phaseless Spherical Near-Field Antenna Measurements.
Sensors 25.18. Sep. 2025. DOI

[133]

N. Derevianko • I. G. Kevrekidis • F. Dietrich
Neural network-based singularity detection and applications.
Preprint (Sep. 2025). arXiv

[132]

P. Esser • M. Fleissner • D. Ghoshdastidar
Theoretical Foundations of Representation Learning using Unlabeled Data: Statistics and Optimization.
Preprint (Sep. 2025). arXiv

[131]

T. Klug
Deep Learning for Image Reconstruction: Data Requirements and its Application to Motion-Correction in MRI.
Dissertation TU München. Aug. 2025. URL

[130]

A. Scagliotti • S. Farinelli
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
Nonlinear Analysis 257.113811. Aug. 2025. DOI

[129]

F. Krahmer • F. Pagginelli Patricio • P. Catala
On a Recovery Method with Approximation Guarantees for Noisy Unlimited Sampling.
Invited Talk @SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. Invited Talk. URL

[128]

S. Dirksen • W. Li • J. Maly
Subspace estimation under coarse quantization.
SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. DOI

[127]

A. Veselovska • J. Prestin
Super-resolution via Prony-Type Polynomials.
SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. DOI

[126]

J. Streit • F. Weindel • R. Heckel
Transformer-Based Decoding in Concatenated Coding Schemes Under Synchronization Errors.
ISIT 2025 - IEEE International Symposium on Information Theory. Ann Arbor, MI, USA, Jul 22-27, 2025. DOI

[125]

A. Scagliotti • S. Farinelli
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
VC 2025 - 16th Viennese Conference on Optimal Control and Dynamic Games. Vienna, Austria, Jul 15-18, 2025. PDF

[124]

J. von Berg • A. Fono • M. Datres • S. Maskey • G. Kutyniok
The Price of Robustness: Stable Classifiers Need Overparameterization.
HiLD @ICML 2025 - Workshop on High-dimensional Learning Dynamics at the 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[123]

P. Fatemi • E. Sharifian • M. H. Yassaee
A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[122]

S. Karnik • A. Veselovska • M. Iwen • F. Krahmer
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[121]

D. A. Nguyen • E. Araya • A. Fono • G. Kutyniok
Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[120]

A. Datar • A. Datar • F. Dietrich • W. Schilders
Systematic Construction of Continuous-Time Neural Networks for Linear Dynamical Systems.
SIAM Journal on Scientific Computing 47.4. Jul. 2025. DOI

[119]

D. Chemnitz • M. Engel • C. Kühn • S.-V. Kuntz
A Dynamical Systems Perspective on the Analysis of Neural Networks.
Preprint (Jul. 2025). arXiv

[118]

J. Li • G. Kutyniok
Expressivity of deep neural networks.
Preprint (Jul. 2025). PDF

[117]

F. Weindel • M. Girsch • R. Heckel
Trace Reconstruction with Language Models.
Preprint (Jul. 2025). arXiv

[116]

F. P. Patricio • F. Krahmer • P. Catala
Stable Retrieval for Unlimited Sampling via Adaptive Local Representations.
SSP 2025 - IEEE Statistical Signal Processing Workshop. Edinburgh, Scotland, Jun 08-11, 2025. DOI

[115]

H. Boche • A. Fono • G. Kutyniok
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement.
Applied and Computational Harmonic Analysis 77.101763. Jun. 2025. DOI

[114]

E. Pozzoli • A. Scagliotti
Approximation of diffeomorphisms for quantum state transfers.
IEEE Control Systems Letters Early Access. Jun. 2025. DOI

[113]

K. Jin • J. Latz • C. Liu • A. Scagliotti
Losing momentum in continuous-time stochastic optimisation.
Journal of Machine Learning Research 26.148. Jun. 2025. URL

[112]

M. Rauscher • A. Scagliotti • F. Pagginelli Patricio
Shortest-path recovery from signature with an optimal control approach.
Mathematics of Control, Signals, and Systems 37. Jun. 2025. DOI

[111]

S. Maskey • G. Kutyniok • R. Levie
Generalization Bounds for Message Passing Networks on Mixture of Graphons.
SIAM Journal on Mathematics of Data Science 7.2. Jun. 2025. DOI

[110]

S. Almi • M. Fornasier • J. Klemenc • A. Scagliotti
Balanced quasistatic evolutions of critical points in metric spaces.
Preprint (Jun. 2025). arXiv

[109]

A. Bergmeister • M. K. Lal • S. Jegelka • S. Sra
A projection-based framework for gradient-free and parallel learning.
Preprint (Jun. 2025). arXiv

[108]

C. Kühn • S.-V. Kuntz
Analysis of the Geometric Structure of Neural Networks and Neural ODEs via Morse Functions.
DS 2025 - SIAM Conference on Applications of Dynamical Systems. Denver, CO, USA, May 11-15, 2025. arXiv URL

[107]

H.-H. Chou • J. Maly • C. M. Verdun • B. Freitas Paulo da Costa • H. Mirandola
Get rid of your constraints and reparametrize: A study in NNLS and implicit bias.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL

[106]

H. Boche • V. Fojtik • A. Fono • G. Kutyniok
Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization.
Journal of Fourier Analysis and Applications 31.35. May. 2025. DOI

[105]

T. Karvonen • G. Santin • T. Wenzel
General superconvergence for kernel-based approximation.
Preprint (May. 2025). arXiv

[104]

C. Kühn • S.-V. Kuntz
The Influence of the Memory Capacity of Neural DDEs on the Universal Approximation Property.
Preprint (May. 2025). arXiv

[103]

P. Scholl • A. Dietrich • S. Wolf • J. Lee • A.-A. Schäffer • G. Kutyniok • M. Iskandar
Interpretable Robotic Friction Learning via Symbolic Regression.
Preprint (May. 2025). arXiv

[102]

C. Bülte • S. Maskey • P. Scholl • J. von Berg • G. Kutyniok
Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall.
Climate Change AI @ICLR 2025 - Workshop on Tackling Climate Change with Machine Learning at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[101]

L. Lux • A. H. Berger • A. Weers • N. Stucki • D. Rückert • U. Bauer • J. C. Paetzold
Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[100]

P. Scholl • K. Bieker • H. Hauger • G. Kutyniok
ParFam -- (Neural Guided) Symbolic Regression Based on Continuous Global Optimization.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL GitHub

[99]

H. Hauger • P. Scholl • G. Kutyniok
Robust identifiability for symbolic recovery of differential equations.
ICASSP 2025 - IEEE International Conference on Acoustics, Speech and Signal Processing. Hyderabad, India, Apr 06-11, 2025. DOI

[98]

J. Kostin • F. Krahmer • D. Stöger
How robust is randomized blind deconvolution via nuclear norm minimization against adversarial noise?
Applied and Computational Harmonic Analysis 76.101746. Apr. 2025. DOI

[97]

C. Cipriani • M. Fornasier • A. Scagliotti
From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI

[96]

M. Fornasier • P. Richtárik • K. Riedl • L. Sun
Consensus-Based Optimization with Truncated Noise.
European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI

[95]

G. Kutyniok
How Can Reliability of Artificial Intelligence Be Ensured?
Harvard Data Science Review 7.2. Apr. 2025. DOI

[94]

M. Fornasier • P. Heid • G. E. Sodini
Approximation Theory, Computing, and Deep Learning on the Wasserstein Space.
Mathematical Models and Methods in Applied Sciences 34.4. Apr. 2025. DOI

[93]

L. Sun
Well-posedness and L1−Lp Smoothing Effect of the Porous Media Equation under Poincaré Inequality.
Preprint (Apr. 2025). arXiv

[92]

F. Weindel • R. Heckel
LLM-Guided Search for Deletion-Correcting Codes.
Preprint (Apr. 2025). arXiv

[91]

F. Krahmer • A. Veselovska
The mathematics of dots and pixels: On the theoretical foundations of image halftoning.
GAMM Mitteilungen 48.1. Mar. 2025. DOI

[90]

M. Herold • J. S. Jehle • F. Krahmer • A. Veselovska
Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis.
International Journal for Uncertainty Quantification 15.4. Mar. 2025. DOI

[89]

C. Bülte • P. Scholl • G. Kutyniok
Probabilistic neural operators for functional uncertainty quantification.
Transactions on Machine Learning Research. Mar. 2025. URL

[88]

M. Fornasier • L. Sun
A PDE Framework of Consensus-Based Optimization for Objectives with Multiple Global Minimizers.
Communications in Partial Differential Equations 50.4. Feb. 2025. DOI

[87]

S. Dirksen • W. Li • J. Maly
Subspace and DOA estimation under coarse quantization.
Preprint (Feb. 2025). arXiv

[86]

M. Fornasier • L. Sun
Regularity and positivity of solutions of the Consensus-Based Optimization equation: unconditional global convergence.
Preprint (Feb. 2025). arXiv

[85]

H. Laus • S. Parkinson • V. Charisopoulos • F. Krahmer • R. Willett
Solving Inverse Problems with Deep Linear Neural Networks: Global Convergence Guarantees for Gradient Descent with Weight Decay.
Preprint (Feb. 2025). arXiv

[84]

M. Fornasier • J. Klemenc • A. Scagliotti
Trade-off Invariance Principle for minimizers of regularized functionals.
Math4AiMl 2025 - 3rd Workshop of UMI Group Mathematics for Artificial Intelligence and Machine Learning. Bari, Italy, Jan 29-31, 2025. arXiv PDF

[83]

A. Scagliotti
Minimax Problems for Ensembles of Control-Affine Systems.
SIAM Journal on Control and Optimization 63.1. Jan. 2025. DOI

[82]

K. Bieker • H. T. Kussaba • P. Scholl • J. Jung • A. Swikir • S. Haddadin • G. Kutyniok
Compositional Construction of Barrier Functions for Switched Impulsive Systems.
CDC 2024 - 63rd IEEE Conference on Decision and Control. Milan, Italy, Dec 16-19, 2024. DOI

[81]

C. Bülte • P. Scholl • G. Kutyniok
Probabilistic predictions with Fourier neural operators.
BDU @NeurIPS 2024 - Workshop Bayesian Decision-making and Uncertainty: from probabilistic and spatiotemporal modeling to sequential experiment design at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[80]

A. Bonfanti • G. Bruno • C. Cipriani
The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[79]

F. Hoppe • C. M. Verdun • H. Laus • F. Krahmer • H. Rauhut
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[78]

R. Paolino • S. Maskey • P. Welke • G. Kutyniok
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[77]

Y. N. Böck • H. Boche • F. H. P. Fitzek • G. Kutyniok
Computing-Model and Computing-Hardware Selection for ICT Under Societal and Judicial Constraints.
IEEE Access 12. Dec. 2024. DOI

[76]

C. Geldhauser • C. Kuehn
Travelling waves for discrete stochastic bistable equations.
Partial Differential Equations and Applications 5.35. Nov. 2024. DOI

[75]

A. Riess • A. Ziller • S. Kolek • D. Rückert • J. A. Schnabel • G. Kaissis
Complex-Valued Federated Learning with Differential Privacy and MRI Applications.
DeCaF @MICCAI 2024 - 5th Workshop on Distributed, Collaborative and Federated Learning at the 27th International Conference on Medical Image Computing and Computer Assisted Intervention. Marrakesh, Morocco, Oct 06-10, 2024. DOI

[74]

A. H. Berger • L. Lux • N. Stucki • V. Bürgin • S. Shit • A. Banaszaka • D. Rückert • U. Bauer • J. C. Paetzold
Topologically faithful multi-class segmentation in medical images.
MICCAI 2024 - 27th International Conference on Medical Image Computing and Computer Assisted Intervention. Marrakesh, Morocco, Oct 06-10, 2024. DOI

[73]

P. Scholl • M. Iskandar • S. Wolf • J. Lee • A. Bacho • A. Dietrich • A. Albu-Schäffer • G. Kutyniok
Learning-based adaption of robotic friction models.
Robotics and Computer-Integrated Manufacturing 89. Oct. 2024. DOI

[72]

P. Scholl • A. Bacho • H. Boche • G. Kutyniok
Symbolic Recovery of Differential Equations: The Identifiability Problem.
Preprint (Oct. 2024). arXiv

[71]

F. Hoppe • C. M. Verdun • H. Laus • S. Endt • M. I. Menzel • F. Krahmer • H. Rauhut
Imaging with Confidence: Uncertainty Quantification for High-dimensional Undersampled MR Images.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub

[70]

Y. Mansour • X. Zhong • S. Caglar • R. Heckel
TTT-MIM: Test-Time Training with Masked Image Modeling for Denoising Distribution Shifts.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub

[69]

K. Riedl
Mathematical Foundations of Interacting Multi-Particle Systems for Optimization.
Dissertation TU München. Sep. 2024. URL

[68]

F. Hoppe • C. M. Verdun • F. Krahmer • M. I. Menzel • H. Rauhut
With or Without Replacement? Improving Confidence in Fourier Imaging.
CoSeRa 2024 - International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging. Santiago de Compostela, Spain, Sep 18-20, 2024. DOI

[67]

F. P. Patricio • P. Catala • F. Krahmer
Noisy Recovery in Unlimited Sampling via Adaptive Modulo Representations.
CoSeRa 2024 - International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging. Santiago de Compostela, Spain, Sep 18-20, 2024. DOI

[66]

P. Römer • F. Krahmer
A one-bit quantization approach for low-dose Poisson phase retrieval.
CoSeRa 2024 - International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging. Santiago de Compostela, Spain, Sep 18-20, 2024. DOI

[65]

C. Geldhauser • K. Malyshev
Semi-automatic annotation of Greek majuscule manuscripts: Steps towards integrated transcription and annotation.
FedCSIS 2024 - 19th Conference on Computer Science and Intelligence Systems. Belgrade, Serbia, Sep 08-11, 2024. DOI

[64]

Ç. Yapar • R. Levie • G. Kutyniok • G. Caire
Dataset of Pathloss and ToA Radio Maps With Localization Application.
Preprint (Sep. 2024). arXiv

[63]

G. Kaissis • S. Kolek • B. Balle • J. Hayes • D. Rückert
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[62]

H. Boche • A. Fono • G. Kutyniok
A Mathematical Framework for Computability Aspects of Algorithmic Transparency.
ISIT 2024 - IEEE International Symposium on Information Theory. Athens, Greece, Jul 07-12, 2024. DOI

[61]

G. M. Nguegnang • H. Rauhut • U. Terstiege
Convergence of gradient descent for learning linear neural networks.
Advances in Continuous and Discrete Models 2024.23. Jul. 2024. DOI

[60]

M. Fornasier • T. Klock • K. Riedl
Consensus-Based Optimization Methods Converge Globally.
SIAM Journal on Optimization 34.3. Jul. 2024. DOI

[59]

C. M. Verdun • O. Melnyk • F. Krahmer • P. Jung
Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence.
COLT 2024 - 37th Annual Conference on Learning Theory. Edmonton, Canada, Jun 30-Jul 03, 2024. URL

[58]

C. Cipriani • A. Scagliotti • T. Wöhrer
A Minimax Optimal Control Approach for Robust Neural ODEs.
ECC 2024 - European Control Conference. Stockholm, Sweden, Jun 25-28, 2024. DOI

[57]

A. Scagliotti • P. Colli Franzone
A subgradient method with constant step-size for l1-composite optimization.
Bollettino dell’Unione Matematica Italiana 17. Jun. 2024. DOI

[56]

Ç. Yapar • F. Jaensch • R. Levie • G. Kutyniok • G. Caire
Overview of the First Pathloss Radio Map Prediction Challenge.
IEEE Open Journal of Signal Processing 5. Jun. 2024. DOI

[55]

M. Brunner • M. Innerberger • A. Miraçi • D. Praetorius • J. Streitberger • P. Heid
Adaptive FEM with quasi-optimal overall cost for nonsymmetric linear elliptic PDEs.
IMA Journal of Numerical Analysis 44.3. May. 2024. DOI

[54]

Y. Lee • H. Boche • G. Kutyniok
Computability of Optimizers.
IEEE Transactions on Information Theory 70.4. Apr. 2024. DOI

[53]

R. Bailo • A. Barbaro • S. N. Gomes • K. Riedl • T. Roith • C. Totzeck • U. Vaes
CBX: Python and Julia packages for consensus-based interacting particle methods.
Preprint (Mar. 2024). arXiv

[52]

B. Lorenz • A. Bacho • G. Kutyniok
Error Estimation for Physics-informed Neural Networks Approximating Semilinear Wave Equations.
Preprint (Mar. 2024). arXiv

[51]

M. Singh • A. Fono • G. Kutyniok
Expressivity of Spiking Neural Networks.
Preprint (Mar. 2024). arXiv

[50]

C. Geldhauser • H. Diebel-Fischer
Is diverse and inclusive AI trapped in the gap between reality and algorithmizability?
NLDL 2024 - Northern Lights Deep Learning Conference. Tromsø, Norway, Jan 09-11, 2024. URL

[49]

T. Yang • J. Maly • S. Dirksen • G. Caire
Plug-In Channel Estimation With Dithered Quantized Signals in Spatially Non-Stationary Massive MIMO Systems.
IEEE Transactions on Communications 72.1. Jan. 2024. DOI

[48]

S. Dirksen • J. Maly
Tuning-free one-bit covariance estimation using data-driven dithering.
Preprint (Jan. 2024). arXiv

[47]

G. Kaissis • A. Ziller • S. Kolek • A. Riess • D. Rückert
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[46]

C. Kümmerle • J. Maly
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[45]

S. Maskey • R. Paolino • A. Bacho • G. Kutyniok
A Fractional Graph Laplacian Approach to Oversmoothing.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI GitHub

[44]

M. Seleznova • D. Weitzner • R. Giryes • G. Kutyniok • H.-H. Chou
Neural (Tangent Kernel) Collapse.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[43]

M. Singh • A. Fono • G. Kutyniok
Are Spiking Neural Networks more expressive than Artificial Neural Networks?
UniReps @NeurIPS 2023 - 1st Workshop on Unifying Representations in Neural Models at the 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. URL

[42]

H. Boche • A. Fono • G. Kutyniok
Limitations of Deep Learning for Inverse Problems on Digital Hardware.
IEEE Transactions on Information Theory 69.12. Dec. 2023. DOI

[41]

Ç. Yapar • R. Levie • G. Kutyniok • G. Caire
Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach.
IEEE Transactions on Wireless Communications 22.12. Dec. 2023. DOI

[40]

J. Maly
Robust sensing of low-rank matrices with non-orthogonal sparse decomposition.
Applied and Computational Harmonic Analysis 67. Nov. 2023. 2024 ACHA Charles Chui Young Researcher Best Paper Award. DOI

[39]

F. Filbir • M. Tasche • A. Veselovska
Regularized Shannon sampling formulas related to the special affine Fourier transform.
Preprint (Nov. 2023). arXiv

[38]

K. Riedl
Leveraging Memory Effects and Gradient Information in Consensus-Based Optimisation: On Global Convergence in Mean-Field Law.
European Journal of Applied Mathematics. Oct. 2023. DOI

[37]

U. Bauer • F. Lenzen
Inferring a Cell Structure on the Space of Cyclooctane Conformations.
MathSEE 2023 - Symposium on Mathematics in Sciences, Engineering and Economics. Karslruhe, Germany, Sep 27-29, 2023. DOI

[36]

F. Hoppe • C. M. Verdun • H. Laus • F. Krahmer • H. Rauhut
Uncertainty Quantification For Learned ISTA.
MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI

[35]

Ç. Yapar • F. Jaensch • R. Ron • G. Kutyniok • G. Caire
Overview of the Urban Wireless Localization Competition.
MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI

[34]

A. Bacho • H. Boche • G. Kutyniok
Complexity Blowup for Solutions of the Laplace and the Diffusion Equation.
Preprint (Sep. 2023). arXiv

[33]

F. Hoppe • F. Krahmer • C. M. Verdun • M. I. Menzel • H. Rauhut
Uncertainty quantification for sparse Fourier recovery.
Preprint (Sep. 2023). arXiv

[32]

S. Endt • M. Engel • E. Naldi • R. Assereto • M. Molendowska • L. Mueller • C. M. Verdun • C. M. Pirkl • M. Palombo • D. K. Jones • M. I. Menzel
In vivo myelin water quantification using diffusion--relaxation correlation MRI: A comparison of 1D and 2D methods.
Applied Magnetic Resonance 54. Aug. 2023. DOI

[31]

P. Heid
A damped Kačanov scheme for the numerical solution of a relaxed p(x)-Poisson equation.
Partial Differential Equations and Applications 4.40. Aug. 2023. DOI

[30]

H.-H. Chou • J. Maly • D. Stöger
How to induce regularization in linear models: A guide to reparametrizing gradient flow.
Preprint (Aug. 2023). arXiv

[29]

N. Stucki • J. C. Paetzold • S. Shit • B. Menze • U. Bauer
Topologically faithful image segmentation via induced matching of persistence barcodes.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL GitHub

[28]

S. Alberti • N. Dern • L. Thesing • G. Kutyniok
Sumformer: Universal Approximation for Efficient Transformers.
TAG-ML @ICML 2023 - 2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning at the 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[27]

T. Fuchs • F. Krahmer • R. Kueng
Greedy-type sparse recovery from heavy-tailed measurements.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

[26]

F. Hoppe • F. Krahmer • C. M. Verdun • M. I. Menzel • H. Rauhut
Sampling Strategies for Compressive Imaging Under Statistical Noise.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

[25]

R. Joy • F. Krahmer • A. Lupoli • R. Ramakrishan
Quantization of Bandlimited Functions Using Random Samples.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

[24]

F. Krahmer • H. Lyu • R. Saab • A. Veselovska • R. Wang
Quantization of Bandlimited Graph Signals.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

[23]

F. Krahmer • A. Veselovska
Digital Halftoning via Mixed-Order Weighted Σ∆ Modulation.
SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

[22]

G. Kutyniok
An introduction to the mathematics of deep learning.
European Congress of Mathematics. Jul. 2023. DOI

[21]

F. Krahmer • A. Veselovska
Enhanced Digital Halftoning via Weighted Sigma-Delta Modulation.
SIAM Journal on Imaging Sciences 16.3. Jul. 2023. DOI

[20]

A. Bacho • H. Boche • G. Kutyniok
Reliable AI: Does the Next Generation Require Quantum Computing?
Preprint (Jul. 2023). arXiv

[19]

Y. Mansour • R. Heckel
Zero-Shot Noise2Noise: Efficient Image Denoising without any Data.
CVPR 2023 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Vancouver, Canada, Jun 18-23, 2023. DOI

[18]

P. Scholl • A. Bacho • H. Boche • G. Kutyniok
The Uniqueness Problem of Physical Law Learning.
ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing. Rhode Island, Greece, Jun 04-10, 2023. DOI

[17]

Ç. Yapar • F. Jaensch • R. Levie • G. Kutyniok • G. Caire
The First Pathloss Radio Map Prediction Challenge.
ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing. Rhode Island, Greece, Jun 04-10, 2023. DOI

[16]

K. Riedl • T. Klock • C. Geldhauser • M. Fornasier
Gradient is All You Need?
Preprint (Jun. 2023). arXiv

[15]

H. Huang • J. Qiu • K. Riedl
On the global convergence of particle swarm optimization methods.
Applied Mathematics and Optimization 88.2. May. 2023. DOI

[14]

R. Paolino • A. Bojchevski • S. Günnemann • G. Kutyniok • R. Levie
Unveiling the Sampling Density in Non-Uniform Geometric Graphs.
ICLR 2023 - 11th International Conference on Learning Representations. Kigali, Rwanda, May 01-05, 2023. URL

[13]

H.-H. Chou • H. Rauhut • R. Ward
Robust implicit regularization via weight normalization.
Preprint (May. 2023). arXiv

[12]

J. Maly • R. Saab
A simple approach for quantizing neural networks.
Preprint (Apr. 2023). arXiv

[11]

P. Heid
A short note on an adaptive damped Newton method for strongly monotone and Lipschitz continuous operator equations.
Archiv der Mathematik. Mar. 2023. URL

[10]

A. Scagliotti
Optimal control of ensembles of dynamical systems.
ESAIM - Control, Optimisation and Calculus of Variations 29.22. Mar. 2023. DOI

[9]

C. M. Verdun
Scalability in Ill-posed Machine Learning Problems: Bridging Least Squares Methods with (Non-)convex Algorithms.
Dissertation TU München. Dec. 2022. URL

[8]

H. Boche • A. Fono • G. Kutyniok
Non-Computability of the Pseudoinverse on Digital Computers.
Preprint (Dec. 2022). arXiv

[7]

H. Huang • J. Qiu • K. Riedl
Consensus-Based Optimization for Saddle Point Problems.
Preprint (Dec. 2022). arXiv

[6]

C. Koke • G. Kutyniok
Graph Scattering beyond Wavelet Shackles.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[5]

S. Maskey • R. Levie • Y. Lee • G. Kutyniok
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[4]

Y. Zhou • G. Kutyniok • B. Ribeiro
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[3]

A. Scagliotti • P. Colli Franzone
Accelerated subgradient methods.
Preprint (Feb. 2022). arXiv

[2]

C. M. Verdun • T. Fuchs • P. Harar • D. Elbrächter • D. S. Fischer • J. Berner • P. Grohs • F. J. Theis • F. Krahmer
Group Testing for SARS-CoV-2 Allows for Up to 10-Fold Efficiency Increase Across Realistic Scenarios and Testing Strategies.
Frontiers in Public Health 9. Aug. 2021. DOI

[1]

A3 | Computational Models

Mathematical models and statistical concepts, which are core elements of ML methods, must be reflected by efficient algorithmic implementations. Furthermore, the execution of corresponding algorithms requires a suitable computational infrastructure. Currently, the steady growth of ML applications brings new algorithmic problems and computational challenges that MCML is addressing in this research area.

Thomas Gabor

Prof. Dr.

Collaborating PI

Technology and Research on Artificial Intelligence

Stephan Günnemann

Prof. Dr.

Core PI

Data Analytics & Machine Learning

Eyke Hüllermeier

Prof. Dr.

Core PI

Artificial Intelligence and Machine Learning

Stefanie Jegelka

Prof. Dr.

Core PI

Foundations of Deep Neural Networks

Niki Kilbertus

Prof. Dr.

Core PI

Ethics in Systems Design and Machine Learning

Johannes Kinder

Prof. Dr.

Collaborating PI

Programming Languages and Artificial Intelligence

Marcus Paradies

Prof. Dr.

Collaborating PI

Database Systems, Data Mining and AI

Steffen Schneider

Dr.

Collaborating PI

Dynamical Inference

Matthias Schubert

Prof. Dr.

Core PI

Spatial Artificial Intelligence

Thomas Seidl

Prof. Dr.

Director

Database Systems, Data Mining and AI

Volker Tresp

Prof. Dr.

Core PI

Database Systems, Data Mining and AI

©all images: LMU | TUM

Publications in Research Area A3

[571]

P. Kolpaczki • F. Edelmann • M. Muschalik • E.
Approximating Shapley Interactions with Marginal Contributions.
ECML-PKDD 2026 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Naples, Italy, Sep 07-11, 2026. To be published.

[570]

X. Gonzalez-Garcia • S. L. Chau • J. Rodemann • M. Caprio • K. Muandet • H. Bustince • S. Destercke • E. Hüllermeier • Y. Sale
Quantification of Credal Uncertainty: A Distance-Based Approach.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. Preprint. arXiv

[569]

S. Haas • L. Killmaier • A. Javanmardi • E. Hüllermeier
Reliable Conformal Prediction for Ordinal Classification Using the Ranked Probability Score.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published.

[568]

[567]

[566]

A. Javanmardi • S. H. Zargarbashi • S. M. A. R. Thies • W. Waegeman • A. Bojchevski • E. Hüllermeier
Optimal Conformal Prediction under Epistemic Uncertainty.
UAI 2026 - 42nd Conference on Uncertainty in Artificial Intelligence. Amsterdam, The Netherlands, Aug 17-21, 2026. To be published. Preprint available. arXiv

[565]

[564]

P. Kolpaczki • E. Hüllermeier
Approximation Algorithms for the Shapley Value: Taxonomy and Properties.
IJCAI-ECAI 2026 - 35th International Joint Conference on Artificial Intelligence. Bremen, Germany, Aug 15-21, 2026. To be published.

[563]

T. Amico • P. Matthews • L. Krieger • A. Zimek • I. Assent
DCFO: Density-Based Counterfactuals for Outliers.
KDD 2026 - 32nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Jeju Island, Republic of Korea, Aug 09-13, 2026. To be published. Preprint available. URL

[562]

[561]

R. Poletukhin • M. Kollovieh • E. Eberhard • S. Günnemann
3D Molecule Generation from Rigid Motifs via SE(3) Flows.
GenBio @ICML 2026 - Workshop on Generative and Agentic AI for Biology at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[560]

[559]

[558]

J. Bi • A. Aniri • M. Yang • X. Zhou • W. Huang • S. Yan • Y. Wang • Z. Cao • M. Färber • X. Xiao • V. Tresp • Y. Ma
EchoRL: Reinforcement Learning via Rollout Echoing.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[557]

J. Bi • D. Yan • Y. Wang • W. Huang • H. Chen • G. Wan • M. Ye • X. Xiao • H. Schütze • V. Tresp • Y. Ma
The Geometry of Reasoning: Self-Evaluation via Layerwise Trajectory Evolution.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[556]

V. Bürgin • D. Herbst • Y.-W. E. Lin • S. Jegelka
Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[555]

W. Durani • P. Jahn • C. Leiber • D. B. Hoffmann • T. Seidl • C. Plant • C. Böhm
CHB: A Diagnostic Toolkit for Hardness-Aware Clustering Evaluation.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[554]

E. S. Eberhard • L. A. Thiede • A. Aldossary • A. Burger • N. Gao • V. Bhethanabotla • A. Aspuru-Guzik • S. Günnemann
Derivative Informed Learning of Exchange-Correlation Functionals.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[553]

L. Gosch • X. Chen • Y. Scholten • S. Günnemann
Certifying Graph Neural Networks Against Label and Structure Poisoning.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[552]

X. Guo • R. Zhou • Y. Wang • Q. Zhang • C. Zhang • S. Jegelka • X. Wang • J. Chai • G. Yin • W. Lin • Y. Wang
SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[551]

A. Kosmala • S. Günnemann • M. Gao • B. M. Wood
Speculative Sampling For Faster Molecular Dynamics.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[550]

T. Liu • C. Qian • M. Cief • Y. He • D. Dan • N. Aletras • G. Kazai
On Effectiveness and Efficiency of Agentic Tool-calling and RL Training.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[549]

[548]

S. Thies • V. Bengs • T. Kaufmann • S. Vollmer • E. Hüllermeier
Calibrated Preference Learning: The Case of Label Ranking.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL GitHub

[547]

T. Tomov • D. Fuchsgruber • S. Günnemann
Task-Awareness Improves LLM Generations and Uncertainty.
ICML 2026 - 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. To be published. Preprint available. URL

[546]

[545]

V. Bürgin • D. Herbst • Y.-W. E. Lin • S. Jegelka
Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability.
WSS @ICML 2026 - Workshop on Weight-Space Symmetries at the 43rd International Conference on Machine Learning. Seoul, South Korea, Jul 06-11, 2026. Oral Presentation. To be published. Preprint available. URL GitHub

[544]

S. Yan • X. Yang • Z. Huang • E. Nie • Z. Ding • Z. Li • X. Ma • J. Bi • K. Kersting • J. Z. Pan • H. Schütze • V. Tresp • Y. Ma
Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning.
ACL 2026 - 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI

[543]

X. Ma • Y. Ma • C. Lin • S. Yan • J. Bi • Z. Cao • Y. Tian • V. Tresp • H. Schütze
Self-Evolving Multi-Agent Systems via Textual Backpropagation.
Findings @ACL 2026 - Findings at the 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026. DOI

[542]

G. M. Tavares • D. Schuster • U. Schlegel • T. Seidl
Explainable AI for Streaming Process Mining: Overview, Challenges and Outlook.
xAI 2026 - 4th World Conference on Explainable Artificial Intelligence. Fortaleza, Brazil, Jul 01-03, 2026. To be published.

[541]

U. Schlegel • T. Seidl
What-If Explanations Over Time: Counterfactuals for Time Series Classification.
xAI 2026 - 4th World Conference on Explainable Artificial Intelligence. Fortaleza, Brazil, Jul 01-03, 2026. To be published. Preprint available. arXiv

[540]

J. Rauscher • F. L. Dennig • U. Schlegel • D. A. Keim • T. Schreck
Visual Boosting Techniques for Spatiotemporal Dense Pixel Visualizations.
EuroVA @EuroVis 2026 - International Workshop on Visual Analytics at the Eurographics Conference on Visualization. Nottingham, UK, Jun 08-12, 2026. DOI

[539]

U. Schlegel • G. M. Tavares • D. Schuster • T. Seidl
From Black-Box to Collaborative: Position Paper on Human-Guided Trace Clustering.
Vipra @EuroVis 2026 - Visual Process Analytics Workshop at the Eurographics Conference on Visualization. Nottingham, UK, Jun 08-12, 2026. DOI

[538]

R. Jimenez • B. Bolliet • F. Villaescusa-Navarro • R. Zbib • B. Wandelt • D. N. Spergel • T. Meier • J. Montgomery • H. Aliee • L. Verde
AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions.
Preprint (Jun. 2026). arXiv

[537]

T. Mortier • A. Javanmardi • Y. Sale • E. Hüllermeier • W. Waegeman
Conformal Prediction in Hierarchical Classification with Constrained Representation Complexity.
AISTATS 2026 - 29th International Conference on Artificial Intelligence and Statistics. Tangier, Morocco, May 02-05, 2026. To be published. Preprint available. arXiv

[536]

P. Kolpaczki • F. Edelmann • M. Muschalik • E.
Approximating Shapley Interactions with Marginal Contributions.
Machine Learning 115.129. May. 2026. DOI

[535]

A. Bergmeister • S. Jegelka • N. Nüsken • C. Domingo-Enrich • J. Pidstrigach
Reinforce Adjoint Matching: Scaling RL Post-Training of Diffusion and Flow-Matching Models.
Preprint (May. 2026). arXiv GitHub

[534]

[533]

Y. Han • Y. Wang • D. Ghoshdastidar • J. Kinder
ALPHA: Active Learning with PAC-Bayesian Theory for Android Malware Detection.
Preprint (May. 2026). URL GitHub

[532]

P. Hofman • T. Löhr • M. Muschalik • Y. Sale • E. Hüllermeier
Efficient Credal Prediction through Decalibration.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL

[531]

J. Lan • Z. Liu • U. Schlegel • R. Zhao • Y. Liu • H. Schütze • M. A. Hedderich • T. Seidl
Human Uncertainty-Aware Data Selection and Automatic Labeling in Visual Question Answering.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[530]

J. Tong • Y. Fan • A. Zhao • Y. Ma • X. Shen
StreamingThinker: Large Language Models Can Think While Reading.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. URL GitHub

[529]

Y. Wu • Y. Wang • Z. Ye • T. Du • S. Jegelka • Y. Wang
When More is Less: Understanding Chain-of-Thought Length in LLMs.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[528]

Y. Zhang • S. Tang • Z. Li • Z. Han • V. Tresp
WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents.
ICLR 2026 - 14th International Conference on Learning Representations. Rio de Janeiro, Brazil, Apr 23-27, 2026. To be published. Preprint available. arXiv

[527]

[526]

S. Valenzuela • J. Kinder
Pretraining on Call Graphs: When Binary Analysis Tasks Profit From Context.
ICPC 2026 - 34th IEEE/ACM International Conference on Program Comprehension. Rio de Janeiro, Brazil, Apr 12-13, 2026. To be published. Preprint available. URL PDF

[525]

E. S. Eberhard • V. Kotsev • T. Güthle • S. Günnemann
Transferable SCF-Acceleration through Solver-Aligned Initialization Learning.
Preprint (Apr. 2026). arXiv GitHub

[524]

K. Hess • D. Frauen • N. Kilbertus • S. Feuerriegel
Debiased neural operators for estimating functionals.
Preprint (Apr. 2026). arXiv

[523]

M. Kollovieh • S. Ayadi • S. Günnemann
Interpolating Discrete Diffusion Models with Controllable Resampling.
Preprint (Apr. 2026). arXiv

[522]

M. S. A. Lee • K. Padh • D. Watson • N. Kilbertus • J. Singh
Fairness under uncertainty in sequential decisions.
Preprint (Apr. 2026). arXiv GitHub

[521]

Y. Liu • J. Han • S. Yan • V. Tresp • Y. Ma
Routing-Free Mixture-of-Experts.
Preprint (Apr. 2026). arXiv GitHub

[520]

A. Maldonado • C. Imenkamp • H. Reiter • T. Seidl • W. Hasselbring • M. Werner • A. Koschmider
Know Your Streams: On the Conceptualization, Characterization, and Generation of Intentional Event Streams.
Preprint (Apr. 2026). arXiv GitHub

[519]

Y. Liu • Y. Ma • Y. Lu • S. Chen • Z. Ding • V. Tresp
Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules.
Findings @EACL 2026 - Findings of the 19th Conference of the European Chapter of the Association for Computational Linguistics. Rabat, Morocco, Mar 24-29, 2026. DOI

[518]

S. Haas • E. Hüllermeier
Aleatoric and Epistemic Uncertainty Measures for Ordinal Classification through Binary Reduction.
Machine Learning 115.63. Mar. 2026. DOI

[517]

N. Schneider • G. Manten • N. Kilbertus
Conservative Continuous-Time Treatment Optimization.
Preprint (Mar. 2026). arXiv

[516]

S. B. Junior • G. M. Tavares • R. S. Oyamada • P. Ceravolo
Encoding Techniques for Digital Trace Data.
Digital Trace Data Research in Information Systems. Feb. 2026. DOI

[515]

M. Aljoud • G. M. Tavares • C. Leiber • T. Seidl
DCMatchBoosted - improving deep clustering by architecture recommendation.
International Journal of Data Science and Analytics 22.58. Feb. 2026. DOI GitHub

[514]

P. Knab • D. Steinmann • C. Bartelt • K. Kersting • B. Schiele • T. Seidl • U. Schlegel • W. Stammer
What’s in the Bottle? A Survey and Roadmap of Concept Bottleneck Models.
Preprint (Feb. 2026). DOI

[513]

A. Pierro • J. Timcheck • J. Yik • M. Lindauer • E. Hüllermeier • M. Wever
Evolutionary Mapping of Neural Networks to Spatial Accelerators.
Preprint (Feb. 2026). arXiv

[512]

K. Yamaoka • S. Mukherjee • T. Gärtner • D. A. Selby • S. Konigorski • E. Hüllermeier • V. Bengs • S. J. Vollmer
Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models.
Preprint (Feb. 2026). arXiv

[511]

U. Schlegel • F. Weeber • J. Lan • T. Seidl
PRSM: A Measure to Evaluate CLIP's Robustness Against Paraphrases.
MMM 2026 - 32nd International Conference on Multimedia Modeling. Prague, Czech Republic, Jan 29-31, 2026. DOI

[510]

H. Chen • J. Li • Y. Zhang • J. Bi • Y. Xia • J. Gu • V. Tresp
AUVIC: Adversarial Unlearning of Visual Concepts for Multi-modal Large Language Models.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[509]

P. Hofman • Y. Sale • E. Hüllermeier
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[508]

G. D. Pelegrina • P. Kolpaczki • E. Hüllermeier
Shapley Value Approximation Based on k-Additive Games.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[507]

N. Walha • S. G. Gruber • T. Decker • Y. Yang • A. Javanmardi • E. Hüllermeier • F. Buettner
Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[506]

Y. Wang • Aniri • J. Bi • S. Pirk • Y. Ma
ASCD: Attention-Steerable Contrastive Decoding for Reducing Hallucination in MLLM.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. DOI

[505]

[504]

Y. Zhang • S. Tang • Z. Li • Z. Han • V. Tresp
WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents.
LaMAS @AAAI 2026 - Workshop on LLM-based Multi-Agent Systems: Towards Responsible, Reliable, and Scalable Agentic Systems at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. URL

[503]

T. Decker • V. Tresp
Towards Quantifying Incompatibilities in Evaluation Metrics for Feature Attributions.
XAI4Science @AAAI 2026 - 2nd Workshop XAI4Science: From Understanding Model Behavior to Discovering New Scientific Knowledge at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. URL

[502]

M. K. Belaid • M. Rabus • E. Hüllermeier
Uncertainty Quantification in Pairwise Difference Learning for Classification.
Machine Learning 115.12. Jan. 2026. DOI

[501]

S. M. A. R. Thies • J. C. Alfaro • V. Bengs
MORE–PLR: Multi-Output Regression Employed for Partial Label Ranking.
Machine Learning 115.18. Jan. 2026. DOI

[500]

[499]

A. Maldonado
Explaining the impact of data characteristics on process mining algorithms.
Dissertation LMU München. Dec. 2025. DOI

[498]

T. Putterman • D. Lim • Y. Gelberg • M. M. Bronstein • S. Jegelka • H. Maron
GL Equivariant Metanetworks for Learning on Low Rank Weight Spaces.
LOG 2025 - 4th Learning on Graphs Conference. Phoenix, AZ, USA, Dec 10-12, 2025. URL

[497]

E. Ailer
Instrumental Variable Methods for Sequential Experiment Design.
Dissertation TU München. Dec. 2025. URL

[496]

V. Margraf • J. Hanselle • J. Rodemann • M. Wever • S. Vollmer • E. Hüllermeier
Imprecise Acquisitions in Bayesian Optimization.
EIML @EurIPS 2025 - Workshop on Epistemic Intelligence in Machine Learning at the European Conference on Information Processing Systems. Copenhagen, Denmark, Dec 03-05, 2025. PDF

[495]

A. Beer • L. Krieger • P. Weber • M. Ritzert • I. Assent • C. Plant
Internal Evaluation of Density-Based Clusterings with Noise.
Preprint (Dec. 2025). arXiv

[494]

S.-V. Bodea • R. G. Laiz • R. H. Williams • M. Gladkova • D. Thalmeier • B. Rieck • F. Sigmund • M. Piraud • A. Wohlschläger • D. Jüstel • A. Stroh • S. Schneider • G. G. Westmeyer
Cortex-Wide Preservation of Multi-Stimulus Information across Degrees of Network Synchronization.
Preprint (Dec. 2025). DOI

[493]

Z. Cai • W. Hua • K. Li • Y. Ma • E. Nie • H. Schütze • K. Stanczak • M. E. Taylor
ICLR 2026 Workshop on Memory for LLM-Based Agentic Systems (MemAgents).
Preprint (Dec. 2025). URL

[492]

J. M. R. de Vargas • K. Padh • N. Kilbertus
Cluster-Dags as Powerful Background Knowledge For Causal Discovery.
Preprint (Dec. 2025). arXiv

[491]

S. Mukherjee • S. Lebedeva • V. Margraf • J. Hanselle • K. Yamaoka • V. Bengs • S. Konigorski • E. Hüllermeier • S. J. Vollmer
Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits.
Preprint (Dec. 2025). arXiv

[490]

S. Rauch • C. M. M. Frey • A. Maldonado • D. Schuster • G. M. Tavares • T. Seidl
Hierarchical Structuring of Bilaterally Expanding Subtrace Patterns for Efficient Tree-based Activity Suffix Prediction.
Preprint (Dec. 2025). DOI

[489]

H. Chen • Y. Zhang • Y. Bi • Y. Zhang • T. Liu • J. Bi • J. Lan • C. Grosser • D. Krompaß • J. Gu • N. Navab • V. Tresp
Does Machine Unlearning Truly Remove Knowledge?
Lock-LLM @NeurIPS 2025 - Lock-LLM Workshop: Prevent Unauthorized Knowledge Use from Large Language Models at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[488]

Y. E. Şahin • N. Kilbertus • S. Becker
Predicting symbolic ODEs from multiple trajectories.
ML4PS @NeurIPS 2025 - Workshop on Machine Learning and the Physical Sciences at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. PDF

[487]

H. Baniecki • M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier • P. Biecek
Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[486]

Z. Cao • X. Zhao • L. Krieger • H. Scharr • I. Assent
LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[485]

J. Choi • H. Lim • S. Schneider • J. Choo
ConceptScope: Characterizing Dataset Bias via Disentangled Visual Concepts.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[484]

C. Damke • E. Hüllermeier
Adjusted Count Quantification Learning on Graphs.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[483]

W. Durani • C. Leiber • K. Durani • C. Plant • C. Böhm
Anomaly Detection by an Ensemble of Random Pairs of Hyperspheres.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[482]

T. Kaufmann • Y. Metz • D. A. Keim • E. Hüllermeier
ResponseRank: Data-Efficient Reward Modeling through Preference Strength Learning.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[481]

M. Kollovieh • N. Fleischmann • F. Guerranti • B. Charpentier • S. Günnemann
TreeGen: A Bayesian Generative Model for Hierarchies.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[480]

K. Sakalyan • A. Palma • F. Guerranti • F. J. Theis • S. Günnemann
Modeling Microenvironment Trajectories on Spatial Transcriptomics with NicheFlow.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[479]

T. Schmidt • S. Schneider • M. Bethge
Equivariance by Contrast: Identifiable Equivariant Embeddings from Unlabeled Finite Group Actions.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[478]

M. Yau • E. Akyürek • J. Mao • J. B. Tenenbaum • S. Jegelka • J. Andreas
Learning Linear Attention in Polynomial Time.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Oral Presentation. URL

[477]

T. Decker • V. Tresp • F. Buettner
Improving Perturbation-based Explanations by Understanding the Role of Uncertainty Calibration.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Spotlight Presentation. URL

[476]

T. Löhr • P. Hofman • F. Mohr • E. Hüllermeier
Credal Prediction based on Relative Likelihood.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. Spotlight Presentation. URL

[475]

S. Chen • Z. Li • Z. Han • B. He • T. Liu • H. Chen • G. Groh • P. Torr • V. Tresp • J. Gu
Deep Research Brings Deeper Harm.
ReliableML @NeurIPS 2025 - Workshop on Reliable ML from Unreliable Data at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL GitHub

[474]

J. Lan • Z. Liu • T. Seidl
Human Uncertainty-Aware Reliable Data Selection and Efficient Annotation for Visual Question Answering.
ReliableML @NeurIPS 2025 - Workshop on Reliable ML from Unreliable Data at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[473]

X. Zhao • L. Krieger • Z. Cao • A. Bangun • H. Scharr • I. Assent
Probabilistic Framework for Robustness of Counterfactual Explanations Under Data Shifts.
ReliableML @NeurIPS 2025 - Workshop on Reliable ML from Unreliable Data at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[472]

S. Chen • Z. Han • H. Chen • B. He • S. Si • J. Wu • P. Torr • V. Tresp • J. Gu
Bag of Tricks for Subverting Reasoning-based Safety Guardrails.
ResponsibleFM @NeurIPS 2025 - Workshop on Socially Responsible and Trustworthy Foundation Models at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL GitHub

[471]

Y. Zhang • Y. Wu • H. Zhang • W. Li • H. Chen • G. Li • Z. Han • V. Tresp
GroundedPRM: Tree-Guided and Fidelity-Aware Process Reward Modeling for Step-Level Reasoning.
SEA @NeurIPS 2025 - Workshop on Scaling Environments for Agents at the 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. URL

[470]

W. Durani • P. Jahn • T. Seidl • C. Plant • C. Böhm
MNN-Closure Meets Local Maxima: A Double-Knee Approach to Anomaly Detection.
ICDM 2025 - 25th IEEE International Conference on Data Mining. Washington DC, USA, Nov 12-15, 2025. DOI

[469]

F. Liu • R. Zhao • S. Chen • G. Li • P. Torr • L. Han • J. Gu
Can an Individual Manipulate the Collective Decisions of Multi-Agents?
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[468]

Z. S. Taghavi • A. Modarressi • Y. Ma • H. Schütze
ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub

[467]

M. Wang • S. Chen • K. Kersting • V. Tresp • Y. Ma
METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[466]

M. Wang • L. Lange • H. Adel • Y. Ma • J. Strötgen • H. Schütze
Language Mixing in Reasoning Language Models: Patterns, Impact, and Internal Causes.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[465]

Y. Zhang • C. Lin • S. Tang • H. Chen • S. Zhou • Y. Ma • V. Tresp
SwarmAgentic: Towards Fully Automated Agentic System Generation via Swarm Intelligence.
EMNLP 2025 - Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub

[464]

H. Chen • S. Szyller • W. Xu • N. Himayat
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models.
Findings @EMNLP 2025 - Findings of the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI GitHub

[463]

[462]

A. Wang • D. Shu • Y. Wang • Y. Ma • M. Du
Improving LLM Reasoning through Interpretable Role-Playing Steering.
Findings @EMNLP 2025 - Findings of the Conference on Empirical Methods in Natural Language Processing. Suzhou, China, Nov 04-09, 2025. DOI

[461]

J. Rauscher • M. Schmidt • U. Schlegel • M. Bieleke • J. Schüler • D. A. Keim
MotiVAtor: Analyzing Physical Activity Study Data in Lab and Life through Visual Analytics.
VAHC @VIS 2025 - 16th workshop on Visual Analytics in Healthcare at the IEEE Visualization Conference. Vienna, Austria, Nov 02-07, 2025. DOI

[460]

P. Gupta • M. Wever • E. Hüllermeier
Information Leakage Detection through Approximate Bayes-optimal Prediction.
Information Sciences 719.122419. Nov. 2025. DOI

[459]

[458]

C. L. Choi • V. Subramaniam • A. Torralba • P. Isola • S. Jegelka
Fairness Aware Reward Optimization.
Preprint (Nov. 2025). PDF

[457]

[456]

T. Hannan • D. Mallios • P. Pathak • F. Sardari • T. Seidl • G. Bertasius • M. Fayyaz • S. Sengupta
DocSLM: A Small Vision-Language Model for Long Multimodal Document Understanding.
Preprint (Nov. 2025). arXiv

[455]

D. Herbst • L. Karbevska • D. Kumar • A. Ahuja • F. G. Nasrabadi • F. Frasca
Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners.
Preprint (Nov. 2025). arXiv

[454]

G. Zhang • M. Ding • J. Wu • R. Liao • V. Tresp
ReEXplore: Improving MLLMs for Embodied Exploration with Contextualized Retrospective Experience Replay.
Preprint (Nov. 2025). arXiv

[453]

H. Chen
Addressing data heterogeneity, scarcity, and training efficiency in privacy-preserving federated learning.
Dissertation LMU München. Oct. 2025. DOI

[452]

A. Maldonado • C. M. M. Frey • S. A. Aryasomayajula • L. Zellner • S. A. Fahrenkrog-Petersen • T. Seidl
SHAining on Process Mining: Explaining Event Log Characteristics Impact on Algorithms.
ICPM 2025 - 7th International Conference on Process Mining. Montevideo, Uruguay, Oct 20-24, 2025. DOI

[451]

U. N. Kanilmaz • G. M. Tavares • R. Oyamada • D. Schuster • T. Seidl
Introducing k-traceoids: A Structure-Preserving Trace Clustering Framework.
ML4PM @ICPM 2025 - 6th International Workshop on Leveraging Machine Learning in Process Mining at the 7th International Conference on Process Mining. Montevideo, Uruguay, Oct 20-24, 2025. PDF

[450]

S. Schmidt • J. Koerner • D. Fuchsgruber • S. Gasperini • F. Tombari • S. Günnemann
Prior2Former - Evidential Modeling of Mask Transformers for Assumption-Free Open-World Panoptic Segmentation.
ICCV 2025 - IEEE/CVF International Conference on Computer Vision. Honolulu, Hawai’i, Oct 19-23, 2025. DOI

[449]

R. Liao • G. Huang • Q. Cheng • T. Seidl • D. Cremers • V. Tresp
When and Where do Events Switch in Multi-Event Video Generation?
LongVid-Foundations @ICCV 2025 - 1st Workshop on Long Multi-Scene Video Foundations: Generation, Understanding and Evaluation at the IEEE/CVF International Conference on Computer Vision. Honolulu, Hawai’i, Oct 19-23, 2025. arXiv

[448]

P. Kolpaczki
Approximating the shapley value and shapley interactions.
Dissertation LMU München. Oct. 2025. DOI

[447]

S. Chen • J. Liu • Z. Han • Y. Xia • D. Cremers • P. Torr • V. Tresp • J. Gu
True Multimodal In-Context Learning Needs Attention to the Visual Context.
COLM 2025 - Conference on Language Modeling. Montreal, Canada, Oct 07-09, 2025. URL GitHub

[446]

M. H. Shaker • E. Hüllermeier
Random Forest Calibration.
Knowledge-Based Systems 328.114143. Oct. 2025. DOI

[445]

P. Foth • L. Gosch • S. Geisler • L. Schwinn • S. Günnemann
Adversarial Robustness of Graph Transformers.
Transactions on Machine Learning Research. Oct. 2025. URL

[444]

M. Bahrami • A. Tejada-Lapuerta • S. Becker • F. S. Hashemi G. • F. J. Theis
scConcept: Contrastive pretraining for technology-agnostic single-cell representations beyond reconstruction.
Preprint (Oct. 2025). DOI

[443]

A. Findeis • T. Kaufmann • E. Hüllermeier • R. Mullins
Feedback Forensics: A Toolkit to Measure AI Personality.
Preprint (Oct. 2025). arXiv GitHub

[442]

T. Hannan • S. Wu • M. Weber • S. Shit • J. Gu • R. Koner • A. Ošep • L. Leal-Taixé • T. Seidl
SVAG-Bench: A Large-Scale Benchmark for Multi-Instance Spatio-temporal Video Action Grounding.
Preprint (Oct. 2025). arXiv

[441]

Z. Li • N. Kilbertus
Graph Distance Based on Cause-Effect Estimands with Latents.
Preprint (Oct. 2025). arXiv

[440]

I. M. Grigore • G. M. Tavares • V. Pasquadibisceglie • S. Barbon Junior
Towards Trace Variant Explainability.
ADBIS 2025 - European Conference on Advances in Databases and Information Systems. Tampere, Finland, Sep 23-26, 2025. DOI

[439]

M. F. Dasdelen • H. Lim • M. Buck • K. S. Götze • C. Marr • S. Schneider
CytoSAE: Interpretable Cell Embeddings for Hematology.
MICCAI 2025 - 28th International Conference on Medical Image Computing and Computer Assisted Intervention. Daejeon, Republic of Korea, Sep 23-27, 2025. DOI GitHub

[438]

C. Damke • E. Hüllermeier
Distribution Matching for Graph Quantification Under Structural Covariate Shift.
ECML-PKDD 2025 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI

[437]

P. Jahn • W. Durani • C. Leiber • A. Beer • T. Seidl
Going Offline: An Evaluation of the Offline Phase in Stream Clustering.
ECML-PKDD 2025 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI GitHub

[436]

[435]

U. Schlegel • G. M. Tavares • T. Seidl
Towards Explainable Deep Clustering for Time Series Data.
TempXAI @ECML-PKDD 2025 - Workshop Explainable AI for Time Series and Data Streams at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Porto, Portugal, Sep 15-19, 2025. DOI

[434]

Y. Sale • A. Javanmardi • E. Hüllermeier
Aleatoric and Epistemic Uncertainty in Conformal Prediction.
COPA 2025 - 14th Symposium on Conformal and Probabilistic Prediction with Applications. Egham, UK, Sep 10-12, 2025. URL

[433]

S. Dutta • T. Kaufmann • G. Glavaš • I. Habernal • K. Kersting • F. Kreuter • M. Mezini • I. Gurevych • E. Hüllermeier • H. Schütze
Problem Solving Through Human-AI Preference-Based Cooperation.
Computational Linguistics 51.4. Sep. 2025. DOI

[432]

S. Haas • E. Hüllermeier
Conformalized prescriptive machine learning for uncertainty-aware automated decision making: the case of goodwill requests.
International Journal of Data Science and Analytics 20.3. Sep. 2025. DOI

[431]

J. Schooling • T. Meier • M. Amutorine
Social Impact of LLMs: The Ups, the Downs and the Uncharted Waters.
Preprint (Sep. 2025). DOI

[430]

F. Villaescusa-Navarro • B. Bolliet • P. Villanueva-Domingo • A. E. Bayer • A. Acquah • C. Amancharla • A. Barzilay-Siegal • P. Bermejo • C. Bilodeau • P. C. Ramírez • M. Cranmer • U. L. França • C. Hahn • Y.-F. Jiang • R. Jimenez • J.-Y. Lee • A. Lerario • O. Mamun • T. Meier • A. A. Ojha • P. Protopapas • S. Roy • D. N. Spergel • P. Tarancón-Álvarez • U. Tiwari • M. Viel • D. Wadekar • C. Wang • B. Y. Wang • L. Xu • Y. Yovel • S. Yue • W.-H. Zhou • Q. Zhu • J. Zou • Í. Zubeldia
The Denario project: Deep knowledge AI agents for scientific discovery.
Preprint (Sep. 2025). arXiv GitHub

[429]

A. Wang • X. Wu • D. Shu • Y. Ma • N. Liu
Enhancing LLM Steering through Sparse Autoencoder-Based Vector Refinement.
Preprint (Sep. 2025). arXiv

[428]

I. M. Grigore • G. M. Tavares • V. Pasquadibisceglie • S. B. Junior
Revealing Trace Variant Shift via Multi-dimensional Profiling and Community-Aware Graph Modeling.
AI4BPM @BPM 2025 - 9th International Workshop in Artificial Intelligence for Business Process Management at the 23rd International Conference on Business Process Management. Seville, Spain, Aug 31-Sep 05, 2025. DOI GitHub

[427]

S. Rauch • C. M. M. Frey • A. Maldonado • T. Seidl
BEST: Bilaterally Expanding Subtrace Tree for Event Sequence Prediction.
BPM 2025 - 23rd International Conference on Business Process Management. Seville, Spain, Aug 31-Sep 05, 2025. DOI

[426]

Y. Sun • M. Hagog • M. Weber • D. Hein • S. Udluft • Y. Ma • V. Tresp
First Experience with Real-Time Control Using Simulated VQC-Based Quantum Policies.
QCE 2025 - IEEE International Conference on Quantum Computing and Engineering. Albuquerque, NM, USA, Aug 31-Sep 05, 2025. DOI

[425]

Y. Sun • M. Hagog • M. Weber • D. Hein • S. Udluft • Y. Ma • V. Tresp
Learning Control with Simulated Variational Quantum Policies in a Surrogate Cart-Pole Environment.
QCE 2025 - IEEE International Conference on Quantum Computing and Engineering. Albuquerque, NM, USA, Aug 31-Sep 05, 2025. DOI

[424]

L. Fichtel • M. Spliethöver • E. Hüllermeier • P. Jimenez • N. Klowait • S. Kopp • A.-C. N. Ngomo • A. Robrecht • I. Scharlau • L. Terfloth • A.-L. Vollmer • H. Wachsmuth
Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues.
SIGDIAL 2025 - 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Avignon, France, Aug 25-27, 2025. URL

[423]

J. Blake • M. Schubert
Aerial Coverage Path Planning in Nuclear Emergencies A Training and Evaluation Environment.
Demonstration Track @IJCAI 2025 - Demonstration Track at the 34th International Joint Conference on Artificial Intelligence. Montreal, Canada, Aug 16-22, 2025. DOI

[422]

T. Benoit • Y. Wang • M. Dannehl • J. Kinder
BLens: Contrastive Captioning of Binary Functions using Ensemble Embedding.
USENIX-Security 2025 - 34th USENIX Security Symposium. Seattle, WA, USA, Aug 13-15, 2025. PDF

[421]

Z. Ding • Y. Li • Y. He • A. Norelli • J. Wu • V. Tresp • Y. Ma • M. Bronstein
DyGMamba: Efficiently Modeling Long-Term Temporal Dependency on Continuous-Time Dynamic Graphs with State Space Models.
TGL @KDD 2025 - Temporal Graph Learning Workshopat the 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Toronto, ON, Canada, Aug 03-07, 2025. URL

[420]

V. Margraf • T. Koerner • A. Tornede • M. Wever
RunAndSchedule2Survive: Algorithm Scheduling Based on Run2Survive.
ACM Transactions on Evolutionary Learning and Optimization 5.3. Aug. 2025. DOI

[419]

R. Lu • J. Bi • Y. Ma • F. Xiao • Y. Du • Y. Tian
MV-Debate: Multi-view Agent Debate with Dynamic Reflection Gating for Multimodal Harmful Content Detection in Social Media.
Preprint (Aug. 2025). arXiv

[418]

H. Yang • J. Lan • Y. Liu • H. Schütze • T. Seidl
Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach.
Preprint (Aug. 2025). arXiv

[417]

J. Bi • Y. Wang • H. Chen • X. Xiao • A. Hecker • V. Tresp • Y. Ma
LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering.
ACL 2025 - 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI

[416]

T. Liu • Z. Lai • J. Wang • G. Zhang • S. Chen • P. Torr • V. Demberg • V. Tresp • J. Gu
Multimodal Pragmatic Jailbreak on Text-to-image Models.
ACL 2025 - 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI GitHub

[415]

T. Liu • X. Yu • W. Zhou • J. Gu • V. Tresp
FocalPO: Enhancing Preference Optimizing by Focusing on Correct Preference Rankings.
ACL 2025 - 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI

[414]

E. Nie • B. Shao • Z. Ding • M. Wang • H. Schmid • H. Schütze
BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning.
ACL 2025 - 63rd Annual Meeting of the Association for Computational Linguistics. Vienna, Austria, Jul 27-Aug 01, 2025. DOI GitHub

[413]

J. Hanselle • A. Javanmardi • T. Oberkofler • Y. Sale • E. Hüllermeier
Conformal Prediction without Nonconformity Scores.
UAI 2025 - 41st Conference on Uncertainty in Artificial Intelligence. Rio de Janeiro, Brazil, Jul 21-25, 2025. URL

[412]

V. Margraf • A. Lappe • M. Wever • C. Benjamins • E. Hüllermeier • M. Lindauer
SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration.
GECCO 2025 - Genetic and Evolutionary Computation Conference. Málaga, Spain, Jul 14-18, 2025. DOI GitHub

[411]

F. Kiwitt • B. Tahmasebi • S. Jegelka
Symmetries in Weight Space Learning: To Retain or Remove?
HiLD @ICML 2025 - Workshop on High-dimensional Learning Dynamics at the 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[410]

W. Durani • T. Nitzl • C. Plant • C. Böhm
Weakly Supervised Anomaly Detection via Dual-Tailed Kernel.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[409]

X. Feng • Z. Jiang • T. Kaufmann • E. Hüllermeier • P. Weng • Y. Zhu
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[408]

M. Lienen • A. Saydemir • S. Günnemann
UnHiPPO: Uncertainty-aware Initialization for State Space Models.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[407]

[406]

A. Soleymani • B. Tahmasebi • S. Jegelka • P. Jaillet
Learning with Exact Invariances in Polynomial Time.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL

[405]

J. Zausinger • L. Pennig • A. Kozina • S. Sdahl • J. Sikora • A. Dendorfer • T. Kuznetsov • M. Hagog • N. Wiedemann • K. Chlodny • V. Limbach • A. Ketteler • T. Prein • V. M. Singh • M. M. Danziger • J. Born
Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL GitHub

[404]

L. Xu • M. Sarkar • A. I. Lonappan • Í. Zubeldia • P. Villanueva-Domingo • S. Casas • C. Fidler • C. Amancharla • U. Tiwari • A. Bayer • C. A. Ekioui • M. Cranmer • A. Dimitrov • J. Fergusson • K. Gandhi • S. Krippendorf • A. Laverick • J. Lesgourgues • A. Lewis • T. Meier • B. Sherwin • K. Surrao • F. Villaescusa-Navarro • C. Wang • X. Xu • B. Bolliet
Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery.
ML4Astro @ICML 2025 - Machine Learning for Astrophysics at the 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. PDF

[403]

Z. Li • X. Han • Y. Li • N. Strauß • M. Schubert
DAWM: Diffusion Action World Models for Offline Reinforcement Learning via Action-Inferred Transitions.
WM @ICML 2025 - Workshop on Building Physically Plausible World Models at the 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. arXiv

[402]

L. Rottkamp
Obtaining, improving and evaluating spatio-temporal information for efficient solutions of mobility problems.
Dissertation LMU München. Jul. 2025. DOI

[401]

S. Heid • J. Kornowicz • J. Hanselle • K. Thommes • E. Hüllermeier
MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making.
xAI 2025 - 3rd World Conference on Explainable Artificial Intelligence. Istanbul, Turkey, Jul 09-11, 2025. DOI

[400]

P. Knab • S. Marton • U. Schlegel • C. Bartelt
Which LIME should I trust? Concepts, Challenges, and Solutions.
xAI 2025 - 3rd World Conference on Explainable Artificial Intelligence. Istanbul, Turkey, Jul 09-11, 2025. DOI GitHub

[399]

P. Kolpaczki • T. Nielen • E. Hüllermeier
Antithetic Sampling for Top-k Shapley Identification.
xAI 2025 - 3rd World Conference on Explainable Artificial Intelligence. Istanbul, Turkey, Jul 09-11, 2025. DOI

[398]

Y. Sale • A. Ramdas
Online Selective Conformal Prediction: Errors and Solutions.
Transactions on Machine Learning Research. Jul. 2025. URL

[397]

R. Kamel • F. Guerranti • S. Geisler • S. Günnemann
SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation.
Preprint (Jul. 2025). arXiv

[396]

T. Meier • K. Khutsishvili
Who Owns the Future? Ways to Understand Power, Technology, and the Moral Commons.
Preprint (Jul. 2025). URL

[395]

T. Liu • Z. Lai • J. Wang • G. Zhang • S. Chen • P. Torr • V. Demberg • V. Tresp • J. Gu
Multimodal Pragmatic Jailbreak on Text-to-image Models.
CVPR 2025 - 2nd Workshop on Responsible Generative AI at the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. Best Paper Award. URL GitHub

[394]

H. Chen • H. Li • Y. Zhang • G. Zhang • J. Bi • P. Torr • J. Gu • D. Krompass • V. Tresp
FedBiP: Heterogeneous One-Shot Federated Learning with Personalized Latent Diffusion Models.
CVPR 2025 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. DOI

[393]

T. Dagès • S. Weber • Y.-W. E. Lin • R. Talmon • D. Cremers • M. Lindenbaum • A. M. Bruckstein • R. Kimmel
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding.
CVPR 2025 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. DOI

[392]

T. Hannan • M. M. Islam • J. Gu • T. Seidl • G. Bertasius
ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos.
CVPR 2025 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. DOI GitHub

[391]

G. Zhang • M. L. A. Fok • J. Ma • Y. Xia • D. Cremers • P. Torr • V. Tresp • J. Gu
Localizing Events in Videos with Multimodal Queries.
CVPR 2025 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. DOI

[390]

M. Aljoud • G. M. Tavares • C. Leiber • T. Seidl
DCMatch - Identify Matching Architectures in Deep Clustering through Meta-Learning.
PAKDD 2025 - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Sydney, Australia, Jun 10-13, 2025. DOI GitHub

[389]

M. Ahmadpanah • M. Gobbi • D. Hedin • J. Kinder • A. Sabelfeld
CodeX: Contextual Flow Tracking for Browser Extensions.
CODASPY 2025 - 15th ACM Conference on Data and Application Security and Privacy. Pittsburgh, PA, USA, Jun 04-06, 2025. DOI

[388]

[387]

T. Kaufmann • P. Weng • V. Bengs • E. Hüllermeier
A Survey of Reinforcement Learning from Human Feedback.
Transactions on Machine Learning Research. Jun. 2025. URL

[386]

A. Bergmeister • M. K. Lal • S. Jegelka • S. Sra
A projection-based framework for gradient-free and parallel learning.
Preprint (Jun. 2025). arXiv

[385]

C. Casolo • S. Becker • N. Kilbertus
Identifiability Challenges in Sparse Linear Ordinary Differential Equations.
Preprint (Jun. 2025). arXiv

[384]

E. S. Escriche • S. Jegelka
Learning equivariant models by discovering symmetries with learnable augmentations.
Preprint (Jun. 2025). arXiv

[383]

G. Zhang • T. Hannan • H. Kleiner • B. Aydemir • X. Xie • J. Lan • T. Seidl • V. Tresp • J. Gu
AViLA: Asynchronous Vision-Language Agent for Streaming Multimodal Data Interaction.
Preprint (Jun. 2025). arXiv

[382]

Y. Zhang • H. Gao • H. Chen • W. Li • Y. Ma • V. Tresp
FedNano: Toward Lightweight Federated Tuning for Pretrained Multimodal Large Language Models.
Preprint (Jun. 2025). arXiv

[381]

M. Dannehl • S. Valenzuela • J. Kinder
Which Instructions Matter the Most: A Saliency Analysis of Binary Function Embedding Models.
DLSP @SPW 2025 - 8th Deep Learning Security and Privacy Workshop at the 46th IEEE Symposium on Security and Privacy. San Francisco, CA, May 15, 2025. DOI

[380]

G. Manten • C. Casolo • S. W. Mogensen • N. Kilbertus
An Asymmetric Independence Model for Causal Discovery on Path Spaces.
CLeaR 2025 - 4th Conference on Causal Learning and Reasoning. Lausanne, Switzerland, May 07-09, 2025. URL

[379]

A. Koebler • T. Decker • I. Thon • V. Tresp • F. Buettner
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL

[378]

J. Bi • D. Yan • Y. Wang • W. Huang • H. Chen • G. Wan • M. Ye • X. Xiao • H. Schütze • V. Tresp • Y. Ma
CoT-Kinetics: A Theoretical Modeling Assessing LRM Reasoning Process.
Preprint (May. 2025). arXiv

[377]

X. Guo • A. Li • Y. Wang • S. Jegelka • Y. Wang
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning.
Preprint (May. 2025). arXiv GitHub

[376]

P. Hofman • Y. Sale • E. Hüllermeier
Uncertainty Quantification with Proper Scoring Rules: Adjusting Measures to Prediction Tasks.
Preprint (May. 2025). arXiv

[375]

J. Lan • Y. Fu • U. Schlegel • G. Zhang • T. Hannan • H. Chen • T. Seidl
My Answer Is NOT 'Fair': Mitigating Social Bias in Vision-Language Models via Fair and Biased Residuals.
Preprint (May. 2025). arXiv

[374]

R. S.-E. Shim • D. De Cristofaro • C. M. Hu • A. Vietti • B. Plank
Languages in Multilingual Speech Foundation Models Align Both Phonetically and Semantically.
Preprint (May. 2025). arXiv

[373]

J. Wang • P. Gupta • I. Habernal • E. Hüllermeier
Is Your Prompt Safe? Investigating Prompt Injection Attacks Against Open-Source LLMs.
Preprint (May. 2025). arXiv

[372]

M. Spliethöver • T. Knebler • F. Fumagalli • M. Muschalik • B. Hammer • E. Hüllermeier • H. Wachsmuth
Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection.
NAACL 2025 - Annual Conference of the North American Chapter of the Association for Computational Linguistics. Albuquerque, NM, USA, Apr 29-May 04, 2025. DOI

[371]

L. Fang • Y. Wang • Z. Liu • C. Zhang • S. Jegelka • J. Gao • B. Ding • Y. Wang
What is Wrong with Perplexity for Long-context Language Modeling?
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL GitHub

[370]

A. Findeis • T. Kaufmann • E. Hüllermeier • S. Albanie • R. D. Mullins
Inverse Constitutional AI: Compressing Preferences into Principles.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL GitHub

[369]

M. Kollovieh • M. Lienen • D. Lüdke • L. Schwinn • S. Günnemann
Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[368]

R. G. Laiz • T. Schmidt • S. Schneider
Self-supervised contrastive learning performs non-linear system identification.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL GitHub

[367]

H. Lim • J. Choi • J. Choo • S. Schneider
Sparse autoencoders reveal selective remapping of visual concepts during adaptation.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[366]

G. Manten • C. Casolo • E. Ferrucci • S. Mogensen • C. Salvi • N. Kilbertus
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[365]

M. Muschalik • F. Fumagalli • P. Frazzetto • J. Strotherm • L. Hermes • A. Sperduti • E. Hüllermeier • B. Hammer
Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[364]

L. Rauchwerger • S. Jegelka • R. Levie
Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[363]

B. Tahmasebi • S. Jegelka
Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[362]

Q. Zhang • Y. Wang • J. Cui • X. Pan • Q. Lei • S. Jegelka • Y. Wang
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[361]

D. Herbst • S. Jegelka
Higher-Order Graphon Neural Networks: Approximation and Cut Distance.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL

[360]

M. Sabanayagam • L. Gosch • S. Günnemann • D. Ghoshdastidar
Exact Certification of (Graph) Neural Networks Against Label Poisoning.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL GitHub

[359]

Z. Li • S. Yan • Y. Ma • Y. Li • X. Lyu • M. Schubert
Beyond Single-Step: Multi-Frame Action-Conditiones Video Generation for Reinforcement Learning Environments.
World Models @ICLR 2025 - Workshop on World Models: Understanding, Modelling and Scaling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[358]

T. Decker • V. Tresp • F. Buettner
Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations.
XAI4Science @ICLR 2025 - Workshop XAI4Science: From Understanding Model Behavior to Discovering New Scientific Knowledge at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

[357]

R. Visser • F. Fumagalli • M. Muschalik • E. Hüllermeier • B. Hammer
Explaining Outliers using Isolation Forest and Shapley Interactions.
ESANN 2025 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium, Apr 23-25, 2025. PDF

[356]

Z. Ding
Inductive representation learning and natural language question answering on temporal knowledge graphs.
Dissertation LMU München. Apr. 2025. DOI

[355]

N. Röhrich • A. Hoffmann • R. Nordsieck • E. Zarbali • A. Javanmardi
Masked Autoencoder Self Pre-Training for Defect Detection in Microelectronics.
Preprint (Apr. 2025). arXiv

[354]

M. Scherbela • N. Gao • P. Grohs • S. Günnemann
Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems.
Preprint (Apr. 2025). arXiv

[353]

G. Zhai • E. P. Örnek • D. Z. Chen • R. Liao • Y. Di • N. Navab • F. Tombari • B. Busam
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion.
Nectar Track @3DV 2025 - Nectar Track at the 12th International Conference on 3D Vision. Singapore, Mar 25-28, 2025. arXiv

[352]

R. Amoroso • G. Zhang • R. Koner • L. Baraldi • R. Cucchiara • V. Tresp
Perceive, Query & Reason: Enhancing Video QA with Question-Guided Temporal Queries.
WACV 2025 - IEEE/CVF Winter Conference on Applications of Computer Vision. Tucson, AZ, USA, Feb 28-Mar 04, 2025. DOI

[351]

S. Chen • Z. Han • B. He • J. Liu • M. Buckley • Y. Qin • P. Torr • V. Tresp • J. Gu
Can Multimodal Large Language Models Truly Perform Multimodal In-Context Learning?
WACV 2025 - IEEE/CVF Winter Conference on Applications of Computer Vision. Tucson, AZ, USA, Feb 28-Mar 04, 2025. DOI URL

[350]

Y. Zhang • H. Chen • A. Frikha • Y. Yang • D. Krompass • G. Zhang • J. Gu • V. Tresp
CL-Cross VQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering.
WACV 2025 - IEEE/CVF Winter Conference on Applications of Computer Vision. Tucson, AZ, USA, Feb 28-Mar 04, 2025. DOI

[349]

S. Gilhuber
Advances in deep active learning and synergies with semi-supervision.
Dissertation LMU München. Feb. 2025. DOI

[348]

H. Chen • D. Krompass • J. Gu • V. Tresp
FedPop: Federated Population-based Hyperparameter Tuning.
AAAI 2025 - 39th Conference on Artificial Intelligence. Philadelphia, PA, USA, Feb 25-Mar 04, 2025. DOI

[347]

X. Feng • Z. Jiang • T. Kaufmann • P. Xu • E. Hüllermeier • P. Weng • Y. Zhu
DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback.
AAAI 2025 - 39th Conference on Artificial Intelligence. Philadelphia, PA, USA, Feb 25-Mar 04, 2025. DOI

[346]

J. Lan • D. Frassinelli • B. Plank
Mind the Uncertainty in Human Disagreement: Evaluating Discrepancies between Model Predictions and Human Responses in VQA.
AAAI 2025 - 39th Conference on Artificial Intelligence. Philadelphia, PA, USA, Feb 25-Mar 04, 2025. DOI

[345]

Z. Li • S. S. Cranganore • N. Youngblut • N. Kilbertus
Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity.
AAAI 2025 - 39th Conference on Artificial Intelligence. Philadelphia, PA, USA, Feb 25-Mar 04, 2025. DOI

[344]

Y. Zhang • Z. Ma • Y. Ma • Z. Han • Y. Wu • V. Tresp
WebPilot: A Versatile and Autonomous Multi-Agent System for Web Task Execution with Strategic Exploration.
AAAI 2025 - 39th Conference on Artificial Intelligence. Philadelphia, PA, USA, Feb 25-Mar 04, 2025. DOI

[343]

J. Hanselle • S. Heid • J. Fürnkranz • E. Hüllermeier
Probabilistic scoring lists for interpretable machine learning.
Machine Learning 114.3. Feb. 2025. DOI

[342]

[341]

E. Ailer • C. L. Müller • N. Kilbertus
Instrumental variable estimation for compositional treatments.
Scientific Reports 15.5158. Feb. 2025. DOI

[340]

J. Bi • Aniri • Y. Wang • D. Yan • W. Huang • Z. Jin • X. Ma • S. Yan • A. Hecker • M. Ye • X. Xiao • H. Schütze • V. Tresp • Y. Ma
PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection.
Preprint (Feb. 2025). arXiv GitHub

[339]

M. Jürgens • T. Mortier • E. Hüllermeier • V. Bengs • W. Waegeman
A calibration test for evaluating set-based epistemic uncertainty representations.
Preprint (Feb. 2025). arXiv

[338]

K. Padh • Z. Li • C. Casolo • N. Kilbertus
Your Assumed DAG is Wrong and Here's How To Deal With It.
Preprint (Feb. 2025). arXiv

[337]

O. Petersen • M. Kollovieh • M. Lienen • S. Günnemann
Discrete Bayesian Sample Inference for Graph Generation.
Preprint (Feb. 2025). arXiv

[336]

G. Zhang • M. Ding • T. Liu • Y. Zhang • V. Tresp
Memory Helps, but Confabulation Misleads: Understanding Streaming Events in Videos with MLLMs.
Preprint (Feb. 2025). arXiv

[335]

N. Strauß
Artificial intelligence for resource allocation tasks.
Dissertation LMU München. Dec. 2024. DOI

[334]

B. Kühbacher • F. Iglesias-Suarez • N. Kilbertus • V. Eyring
Towards Physically Consistent Deep Learning For Climate Model Parameterizations.
ICMLA 2024 - 23rd IEEE International Conference on Machine Learning and Applications. Miami, FL, USA, Dec 18-20, 2024. DOI

[333]

L. Gosch • M. Sabanayagam • D. Ghoshdastidar • S. Günnemann
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks.
AdvML-Frontiers @NeurIPS 2024 - 3rd Workshop on New Frontiers in Adversarial Machine Learning at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[332]

A. Koebler • T. Decker • I. Thon • V. Tresp • F. Buettner
Incremental Uncertainty-aware Performance Monitoring with Labeling Intervention.
BDU @NeurIPS 2024 - Workshop Bayesian Decision-making and Uncertainty: from probabilistic and spatiotemporal modeling to sequential experiment design at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[331]

A. White • A. Büttner • M. Gelbrecht • N. Kilbertus • F. Hellmann • N. Boers
Projected Neural Differential Equations for Power Grid Modeling with Constraints.
D3S3 @NeurIPS 2024 - Workshop on Data-driven and Differentiable Simulations, Surrogates, and Solvers at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

[330]

E. Ailer • N. Dern • J. Hartford • N. Kilbertus
Targeted Sequential Indirect Experiment Design.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[329]

[328]

A. Javanmardi • D. Stutz • E. Hüllermeier
Conformalized Credal Set Predictors.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[327]

M. Kollovieh • B. Charpentier • D. Zügner • S. Günnemann
Expected Probabilistic Hierarchies.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[326]

G. Ma • Y. Wang • D. Lim • S. Jegelka • Y. Wang
A Canonicalization Perspective on Invariant and Equivariant Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[325]

M. Muschalik • H. Baniecki • F. Fumagalli • P. Kolpaczki • B. Hammer • E. Hüllermeier
shapiq: Shapley Interactions for Machine Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[324]

Y. Wang • K. Hu • S. Gupta • Z. Ye • Y. Wang • S. Jegelka
Understanding the Role of Equivariance in Self-supervised Learning.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[323]

Y. Wang • Y. Wu • Z. Wei • S. Jegelka • Y. Wang
A Theoretical Understanding of Self-Correction through In-context Alignment.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[322]

D. Winkel • N. Strauß • M. Bernhard • Z. Li • T. Seidl • M. Schubert
Autoregressive Policy Optimization for Constrained Allocation Tasks.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI GitHub

[321]

M. Yau • N. Karalias • E. Lu • J. Xu • S. Jegelka
Are Graph Neural Networks Optimal Approximation Algorithms?
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. DOI

[320]

C. Leiber • N. Strauß • M. Schubert • T. Seidl
Dying Clusters Is All You Need -- Deep Clustering With an Unknown Number of Clusters.
DLC 2024 @ICDM 2024 - 6th Workshop on Deep Learning and Clustering at the 24th IEEE International Conference on Data Mining. Abu Dhabi, United Arab Emirates, Dec 09-12, 2024. DOI GitHub

[319]

M. Bernhard
Deep learning methods for image recognition in remote sensing.
Dissertation LMU München. Dec. 2024. DOI

[318]

A. Beer • P. Weber • L. Miklautz • C. Leiber • W. Durani • C. Böhm • C. Plant
SHADE: Deep Density-based Clustering.
ICDM 2024 - 24th IEEE International Conference on Data Mining. Abu Dhabi, United Arab Emirates, Dec 09-12, 2024. DOI

[317]

T. Hannan • R. Koner • M. Bernhard • S. Shit • B. Menze • V. Tresp • M. Schubert • T. Seidl
GRAtt-VIS: Gated Residual Attention for Video Instance Segmentation.
ICPR 2020 - 27th International Conference on Pattern Recognition. Kolkata, India, Dec 01-05, 2024. DOI GitHub

[316]

N. Saberi • M. H. Shaker • C. R. Duguay • K. A. Scott • E. Hüllermeier
Uncertainty Estimation of Lake Ice Cover Maps From a Random Forest Classifier Using MODIS TOA Reflectance Data.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 18. Dec. 2024. DOI

[315]

M. Kollovieh • L. Gosch • M. Lienen • Y. Scholten • L. Schwinn • S. Günnemann
Assessing Robustness via Score-Based Adversarial Image Generation.
Transactions on Machine Learning Research. Dec. 2024. URL

[314]

F. Fumagalli • M. Muschalik • E. Hüllermeier • B. Hammer • J. Herbinger
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory.
Preprint (Dec. 2024). arXiv

[313]

Y. Liu • Y. Zhang • Q. Li • T. Liu • S. Feng • D. Wang • Y. Zhang • H. Schütze
HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy.
EMNLP 2024 - Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI

[312]

Z. Ding • J. Wu • J. Wu • Y. Xia • V. Tresp
Temporal Fact Reasoning over Hyper-Relational Knowledge Graphs.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI

[311]

R. Liao • M. Erler • H. Wang • G. Zhai • G. Zhang • Y. Ma • V. Tresp
VideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMs.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI GitHub

[310]

H. Zhang • J. Liu • Z. Han • S. Chen • B. He • V. Tresp • Z. Xu • J. Gu
Visual Question Decomposition on Multimodal Large Language Models.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI

[309]

I. M. Grigore • G. M. Tavares • S. Barbon Junior
Beyond Flattening: Detecting Concurrency Anomalies Using K-NN Graph-Based Modeling in Object-Centric Event Logs.
DATAMOD @SEFM 2024 - 12th International Symposium From Data to Models and Back at the 22nd International Conference of Software Engineering and Formal Methods. Aveiro, Portugal, Nov 04-05, 2024. DOI

[308]

M. Bernhard • T. Hannan • N. Strauß • M. Schubert
Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing Images.
ECAI 2024 - 27th European Conference on Artificial Intelligence. Santiago de Compostela, Spain, Oct 19-24, 2024. DOI GitHub

[307]

S. M. A. R. Thies • J. C. Alfaro • V. Bengs
MORE–PLR: Multi-Output Regression Employed for Partial Label Ranking.
DS 2024 - 27th International Conference on Discovery Science. Pisa, Italy, Oct 14-16, 2024. DOI GitHub

[306]

A. Maldonado • S. A. Aryasomayajula • C. M. M. Frey • T. Seidl
iGEDI: interactive Generating Event Data with Intentional Features.
Demo Tracks @ICPM 2024 - Demo Tracks at the 6th International Conference on Process Mining. Lyngby, Denmark, Oct 14-18, 2024. URL

[305]

A. Maldonado
Data-Driven Approaches Towards Transparent Benchmarking of Process Mining Tasks.
Doctoral Consortium @ICPM 2024 - Doctoral Consortium at the 6th International Conference on Process Mining. Lyngby, Denmark, Oct 14-18, 2024. URL

[304]

S. Rauch • C. M. M. Frey • L. Zellner • T. Seidl
Process-Aware Bayesian Networks for Sequential Event Log Queries.
ICPM 2024 - 6th International Conference on Process Mining. Lyngby, Denmark, Oct 14-18, 2024. DOI

[303]

Z. Xian • L. Zellner • G. M. Tavares • T. Seidl
CC-HIT: Creating Counterfactuals from High-Impact Transitions.
ML4PM @ICPM 2024 - 5th International Workshop on Leveraging Machine Learning in Process Mining at the 6th International Conference on Process Mining. Lyngby, Denmark, Oct 14-18, 2024. DOI

[302]

[301]

S. Haas • K. Hegestweiler • M. Rapp • M. Muschalik • E. Hüllermeier
Stakeholder-centric explanations for black-box decisions: an XAI process model and its application to automotive goodwill assessments.
Frontiers in Artificial Intelligence 7. Oct. 2024. DOI

[300]

K. Gatmiry • Z. Li • S. J. Reddi • S. Jegelka
Simplicity Bias via Global Convergence of Sharpness Minimization.
Preprint (Oct. 2024). arXiv

[299]

K. Gatmiry • N. Saunshi • S. J. Reddi • S. Jegelka • S. Kumar
On the Role of Depth and Looping for In-Context Learning with Task Diversity.
Preprint (Oct. 2024). arXiv

[298]

T. Putterman • D. Lim • Y. Gelberg • S. Jegelka • H. Maron
Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models.
Preprint (Oct. 2024). arXiv

[297]

T. Schwarz • C. Casolo • N. Kilbertus
Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series.
Preprint (Oct. 2024). arXiv

[296]

Y. Sun • Z. Wu • Y. Ma • V. Tresp
Quantum Architecture Search with Unsupervised Representation Learning.
Preprint (Oct. 2024). arXiv

[295]

A. White • A. Büttner • M. Gelbrecht • V. Duruisseaux • N. Kilbertus • F. Hellmann • N. Boers
Projected Neural Differential Equations for Learning Constrained Dynamics.
Preprint (Oct. 2024). arXiv

[294]

T. Hannan • M. M. Islam • T. Seidl • G. Bertasius
RGNet: A Unified Clip Retrieval and Grounding Network for Long Videos.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub

[293]

G. Zhai • E. P. Örnek • D. Z. Chen • R. Liao • Y. Di • N. Navab • F. Tombari • B. Busam
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion.
ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI

[292]

M. C. da Silva • B. Licari • G. M. Tavares • S. Barbon Junior
Benchmarking AutoML Clustering Frameworks.
ABCD Track @AutoML 2024 - Track on Applications, Benchmarks, Challenges, and Datasets at the International Conference on Automated Machine Learning. Paris, France, Sep 09-12, 2024. URL

[291]

C. Damke • E. Hüllermeier
CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[290]

R. Fischer • M. Wever • S. Buschjäger • T. Liebig
MetaQuRe: Meta-learning from Model Quality and Resource Consumption.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[289]

S. Gilhuber • A. Beer • Y. Ma • T. Seidl
FALCUN: A Simple and Efficient Deep Active Learning Strategy.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

[288]

P. Jahn • C. M. M. Frey • A. Beer • C. Leiber • T. Seidl
Data with Density-Based Clusters: A Generator for Systematic Evaluation of Clustering Algorithms.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI GitHub

[287]

Y. Liu • E. Nie • S. Feng • Z. Hua • Z. Ding • D. Wang • Y. Zhang • H. Schütze
A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation.
ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI GitHub

[286]

[285]

B. Chocholaty • C. Leiber • S. Marburg
Effects of similarity measures and assignment methods on mode pairing for the application of timber plates.
ISMA 2024 - 31st International Conference on Noise and Vibration Engineering. KU Leuven, Belgium, Sep 09-11, 2024. URL

[284]

M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier
Explaining Change in Models and Data with Global Feature Importance and Effects.
TempXAI @ECML-PKDD 2024 - Tutorial-Workshop Explainable AI for Time Series and Data Streams at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. PDF

[283]

A. Maldonado • C. M. M. Frey • G. M. Tavares • N. Rehwald • T. Seidl
GEDI: Generating Event Data with Intentional Features for Benchmarking Process Mining.
BPM 2024 - 22nd International Conference on Business Process Management. Krakow, Poland, Sep 01-06, 2024. DOI

[282]

R. S. Oyamada • G. M. Tavares • S. B. Junior • P. Ceravolo
CoSMo: A Framework to Instantiate Conditioned Process Simulation Models.
BPM 2024 - 22nd International Conference on Business Process Management. Krakow, Poland, Sep 01-06, 2024. DOI

[281]

P. Kolpaczki • E. Hüllermeier • V. Bengs
Piecewise-Stationary Dueling Bandits.
Transactions on Machine Learning Research. Sep. 2024. URL

[280]

M. C. da Silva • G. M. Tavares • E. Medvet • S. Barbon Junior
Problem-oriented AutoML in Clustering.
Preprint (Sep. 2024). arXiv

[279]

T. Decker • A. Koebler • M. Lebacher • I. Thon • V. Tresp • F. Buettner
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance.
KDD 2024 - 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Barcelona, Spain, Aug 25-29, 2024. DOI

[278]

T. Liu • I. Škrjanec • V. Demberg
Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the 'right reasons'?
ACL 2024 - 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024. DOI

[277]

A. Stephan • L. Miklautz • C. Leiber • P. H. Araujo • D. Répás • C. Plant • B. Roth
Text-Guided Alternative Image Clustering.
RepL4NLP-2024 @ACL 2024 - 9th Workshop on Representation Learning for NLP at the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024. URL

[276]

J. Brandt • M. Wever • V. Bengs • E. Hüllermeier
Best Arm Identification with Retroactively Increased Sampling Budget for More Resource-Efficient HPO.
IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence. Jeju, Korea, Aug 03-09, 2024. DOI

[275]

[274]

S. Heid • J. Hanselle • J. Fürnkranz • E. Hüllermeier
Learning decision catalogues for situated decision making: The case of scoring systems.
International Journal of Approximate Reasoning 171. Aug. 2024. DOI

[273]

A. Szałata • K. Hrovatin • S. Becker • A. Tejada-Lapuerta • H. Cui • B. Wang • F. J. Theis
Transformers in single-cell omics: a review and new perspectives.
Nature Methods 21. Aug. 2024. DOI

[272]

P. Foth • L. Gosch • S. Geisler • L. Schwinn • S. Günnemann
Relaxing Graph Transformers for Adversarial Attacks.
Differentiable Almost Everything @ICML 2024 - Workshop Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. PDF

[271]

Y. Sun • J. Liu • Z. Wu • Z. Ding • Y. Ma • T. Seidl • V. Tresp
SA-DQAS: Self-attention Enhanced Differentiable Quantum Architecture Search.
Differentiable Almost Everything @ICML 2024 - Workshop Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. PDF

[270]

T. Decker • A. R. Bhattarai • J. Gu • V. Tresp • F. Buettner
Provably Better Explanations with Optimized Aggregation of Feature Attributions.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[269]

F. Fumagalli • M. Muschalik • P. Kolpaczki • E. Hüllermeier • B. Hammer
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[268]

[267]

Y. Sale • V. Bengs • M. Caprio • E. Hüllermeier
Second-Order Uncertainty Quantification: A Distance-Based Approach.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[266]

X. Feng • Z. Jiang • T. Kaufmann • E. Hüllermeier • P. Weng • Y. Zhu
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries.
MHFAIA @ICML 2024 - Workshop on Models of Human Feedback for AI Alignment at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[265]

P. Hofman • Y. Sale • E. Hüllermeier
Quantifying Aleatoric and Epistemic Uncertainty: A Credal Approach.
SPIGM @ICML 2024 - Workshop on Structured Probabilistic Inference & Generative Modeling at the 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL

[264]

L. Arrighi • L. Pennella • G. M. Tavares • S. Barbon Junior
Decision Predicate Graphs: Enhancing Interpretability in Tree Ensembles.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI

[263]

P. Kolpaczki • G. Haselbeck • E. Hüllermeier
How Much Can Stratification Improve the Approximation of Shapley Values?
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI

[262]

C. Damke • E. Hüllermeier
Linear Opinion Pooling for Uncertainty Quantification on Graphs.
UAI 2024 - 40th Conference on Uncertainty in Artificial Intelligence. Barcelona, Spain, Jul 16-18, 2024. URL GitHub

[261]

[260]

T. Löhr • M. Ingrisch • E. Hüllermeier
Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification.
AIME 2024 - 22nd International Conference on Artificial Intelligence in Medicine. Salt Lake City, UT, USA, Jul 09-12, 2024. DOI

[259]

A. Javanmardi • O. K. Aimiyekagbon • A. Bender • J. K. Kimotho • W. Sextro • E. Hüllermeier
Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions.
PHME 2024 - 8th European Conference of the Prognostics and Health Management Society 2024. Prague, Czech Republic, Jul 03-05, 2024. DOI

[258]

F. Quinzan • C. Casolo • K. Muandet • Y. Luo • N. Kilbertus
Learning Counterfactually Invariant Predictors.
Transactions on Machine Learning Research. Jul. 2024. URL

[257]

J. Brandt • B. Haddenhorst • V. Bengs • E. Hüllermeier
Dueling Bandits with Delayed Feedback.
DataNinja sAIOnARA 2024 - DataNinja sAIOnARA Conference: Shaping Trustworthy AI: Opportunities, Innovation and Achievements for Reliable Approaches. Bielefeld, Germany, Jun 25-27, 2024. DOI

[256]

H. Li • C. Shen • P. Torr • V. Tresp • J. Gu
Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation.
CVPR 2024 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA, Jun 17-21, 2024. DOI GitHub

[255]

Y. Xia • L. Shi • Z. Ding • J. F. Henriques • D. Cremers
Text2Loc: 3D Point Cloud Localization from Natural Language.
CVPR 2024 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA, Jun 17-21, 2024. DOI GitHub

[254]

I. Obadic • A. Levering • L. Pennig • D. Oliveira • D. Marcos • X. Zhu
Contrastive Pretraining for Visual Concept Explanations of Socioeconomic Outcomes.
Workshop @CVPR 2024 - Workshop at the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA, Jun 17-21, 2024. DOI

[253]

R. Liao • X. Jia • Y. Li • Y. Ma • V. Tresp
GenTKG: Generative Forecasting on Temporal Knowledge Graph with Large Language Models.
Findings @NAACL 2024 - Findings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Mexico City, Mexico, Jun 16-21, 2024. DOI GitHub

[252]

Z. Ding • H. Cai • J. Wu • Y. Ma • R. Liao • B. Xiong • V. Tresp
zrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models.
NAACL 2024 - Annual Conference of the North American Chapter of the Association for Computational Linguistics. Mexico City, Mexico, Jun 16-21, 2024. DOI

[251]

E. Hüllermeier
On the Challenge of Quantifying Epistemic Uncertainty in Machine Learning.
SIPTA - The Society for Imprecise Probabilities: Theories and Applications. Virtual, Jun 14, 2024. Invited Talk. PDF

[250]

R. S. Oyamada • G. M. Tavares • S. B. Junior • P. Ceravolo
Enhancing Predictive Process Monitoring with Time-Related Feature Engineering.
CAiSE 2024 - 36th International Conference on Advanced Information Systems Engineering. Limassol, Cyprus, Jun 03-07, 2024. DOI

[249]

T. Kaufmann • J. Blüml • A. Wüst • Q. Delfosse • K. Kersting • E. Hüllermeier
OCALM: Object-Centric Assessment with Language Models.
Preprint (Jun. 2024). arXiv

[248]

V. Margraf • M. Wever • S. Gilhuber • G. M. Tavares • T. Seidl • E. Hüllermeier
ALPBench: A Benchmark for Active Learning Pipelines on Tabular Data.
Preprint (Jun. 2024). arXiv GitHub

[247]

T. Wollschläger • N. Kemper • L. Hetzel • J. Sommer • S. Günnemann
Expressivity and Generalization: Fragment-Biases for Molecular GNNs.
Preprint (Jun. 2024). arXiv

[246]

Y. Han • Z. Ding • Y. Liu • B. He • V. Tresp
Critical Path Identification in Supply Chain Knowledge Graphs with Large Language Models.
ESWC 2024 - Extended Semantic Web Conference. Hersonissos, Crete, Greece, May 26-30, 2024. DOI

[245]

A. Beer • O. Palotás • A. Maldonado • A. Draganov • I. Assent
DROPP: Structure-aware PCA for Ordered Data.
ICDE 2024 - 40th IEEE International Conference on Data Engineering. Utrecht, Netherlands, May 13-17, 2024. DOI

[244]

S. d'Ascoli • S. Becker • P. Schwaller • A. Mathis • N. Kilbertus
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL GitHub

[243]

L. Eyring • D. Klein • T. Uscidda • G. Palla • N. Kilbertus • Z. Akata • F. J. Theis
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation.
ICLR 2024 - 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[242]

[241]

S. Chen • Z. Han • B. He • M. Buckley • P. Torr • V. Tresp • J. Gu
Understanding and Improving In-Context Learning on Vision-language Models.
ME-FoMo @ICLR 2024 - Workshop on Mathematical and Empirical Understanding of Foundation Models at the 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[240]

Z. Li • S. S. Cranganore • N. Youngblut • N. Kilbertus
Whole Genome Transformers for Gene Interaction Effects in Microbiome Habitat Prediction.
MLGenX @ICLR 2024 - Workshop Machine Learning for Genomics Explorations at the 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[239]

L. Zellner • S. Rauch • J. Sontheim • T. Seidl
On Diverse and Precise Recommendations for Small and Medium-Sized Enterprises.
PAKDD 2024 - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Taipeh, Taiwan, May 07-10, 2024. DOI GitHub

[238]

S. Chen • Z. Han • B. He • Z. Ding • W. Yu • P. Torr • V. Tresp • J. Gu
Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?
SeT LLM @ICLR 2024 - Workshop on Secure and Trustworthy Large Language Models at the 12th International Conference on Learning Representations. Vienna, Austria, May 07-11, 2024. URL

[237]

V. Bengs • B. Haddenhorst • E. Hüllermeier
Identifying Copeland Winners in Dueling Bandits with Indifferences.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL

[236]

P. Kolpaczki • M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL

[235]

A. Lohrer • D. Kazempour • M. Hünemörder • P. Kröger
CoMadOut—a robust outlier detection algorithm based on CoMAD.
Machine Learning 113. May. 2024. DOI

[234]

N. Strauß • M. Schubert
Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem.
SDM 2024 - SIAM International Conference on Data Mining. Houston, TX, USA, Apr 18-20, 2024. DOI

[233]

C. Leiber
Clustering in transformed feature spaces by analyzing distinct modes.
Dissertation LMU München. Apr. 2024. DOI

[232]

I. M. Grigore • G. M. Tavares • M. C. Silva • P. Ceravolo • S. Junior
Automated Trace Clustering Pipeline Synthesis in Process Mining.
Information 15.4. Apr. 2024. DOI

[231]

[230]

P. Hofman • Y. Sale • E. Hüllermeier
Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring Rules.
Preprint (Apr. 2024). arXiv

[229]

L. Rottkamp • M. Schubert
A Time-Inhomogeneous Markov Model for Resource Availability under Sparse Observations.
Preprint (Apr. 2024). arXiv

[228]

H. Chen • Y. Zhang • D. Krompass • J. Gu • V. Tresp
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning.
AAAI 2024 - 38th Conference on Artificial Intelligence. Vancouver, Canada, Feb 20-27, 2024. DOI

[227]

P. Kolpaczki • V. Bengs • M. Muschalik • E. Hüllermeier
Approximating the Shapley Value without Marginal Contributions.
AAAI 2024 - 38th Conference on Artificial Intelligence. Vancouver, Canada, Feb 20-27, 2024. DOI

[226]

J. Lienen • E. Hüllermeier
Mitigating Label Noise through Data Ambiguation.
AAAI 2024 - 38th Conference on Artificial Intelligence. Vancouver, Canada, Feb 20-27, 2024. DOI

[225]

M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.
AAAI 2024 - 38th Conference on Artificial Intelligence. Vancouver, Canada, Feb 20-27, 2024. DOI

[224]

M. Bernhard • R. Amoroso • Y. Kindermann • M. Schubert • L. Baraldi • R. Cucchiara • V. Tresp
What's Outside the Intersection? Fine-grained Error Analysis for Semantic Segmentation Beyond IoU.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub

[223]

U. Sahin • H. Li • Q. Khan • D. Cremers • V. Tresp
Enhancing Multimodal Compositional Reasoning of Visual Language Models With Generative Negative Mining.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub

[222]

G. Zhang • Y. Zhang • K. Zhang • V. Tresp
Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub

[221]

E. Hüllermeier • R. Slowinski
Preference learning and multiple criteria decision aiding: Differences, commonalities, and synergies -- Part I.
4OR. Jan. 2024. DOI

[220]

E. Hüllermeier • R. Slowinski
Preference learning and multiple criteria decision aiding: Differences, commonalities, and synergies -- Part II.
4OR. Jan. 2024. DOI

[219]

S. Chen • J. Gu • Z. Han • Y. Ma • P. Torr • V. Tresp
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI GitHub

[218]

F. Fumagalli • M. Muschalik • P. Kolpaczki • E. Hüllermeier • B. Hammer
SHAP-IQ: Unified Approximation of any-order Shapley Interactions.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[217]

Y. Scholten • J. Schuchardt • A. Bojchevski • S. Günnemann
Hierarchical randomized smoothing.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[216]

J. Schuchardt • Y. Scholten • S. Günnemann
Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More.
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. DOI

[215]

R. Liao • X. Jia • Y. Ma • V. Tresp
GenTKG: Generative Forecasting on Temporal Knowledge Graph.
TGL 2023 @NeurIPS 2023 - Workshop Temporal Graph Learning at the 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. URL

[214]

A. Koebler • T. Decker • M. Lebacher • I. Thon • V. Tresp • F. Buettner
Towards Explanatory Model Monitoring.
XAIA 2023 @NeurIPS 2023 - Workshop XAI in Action: Past, Present, and Future Applications at the 37th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Dec 10-16, 2023. URL

[213]

C. Leiber • L. Miklautz • C. Plant • C. Böhm
Benchmarking Deep Clustering Algorithms With ClustPy.
Workshop @ICDM 2023 - Workshop at the 23rd IEEE International Conference on Data Mining. Shanghai, China, Dec 01-04, 2023. DOI GitHub

[212]

Y. Sale • P. Hofman • L. Wimmer • E. Hüllermeier • T. Nagler
Second-Order Uncertainty Quantification: Variance-Based Measures.
Preprint (Dec. 2023). arXiv

[211]

E. Thelisson • G. Mika • Q. Schneiter • K. Padh • H. Verma
Toward Responsible AI Use: Considerations for Sustainability Impact Assessment.
Preprint (Dec. 2023). arXiv

[210]

G. Zhang • J. Bi • J. Gu • Y. Chen • V. Tresp
SPOT! Revisiting Video-Language Models for Event Understanding.
Preprint (Dec. 2023). arXiv

[209]

Z. Ding • Z. Li • R. Qi • J. Wu • B. He • Y. Ma • Z. Meng • S. Chen • R. Liao • Z. Han • V. Tresp
FORECASTTKGQUESTIONS: A Benchmark for Temporal Question Answering and Forecasting over Temporal Knowledge Graphs.
ISWC 2023 - 22nd International Semantic Web Conference. Athens, Greeke, Nov 06-11, 2023. DOI

[208]

A. Maldonado • G. M. Tavares • R. Oyamada • P. Ceravolo • T. Seidl
FEEED: Feature Extraction from Event Data.
Doctoral Consortium @ICPM 2023 - Doctoral Consortium at the 5th International Conference on Process Mining. Rome, Italy, Oct 23-27, 2023. PDF

[207]

A. Maldonado • L. Zellner • S. Strickroth • T. Seidl
Process Mining Techniques for Collusion Detection in Online Exams.
EduPM @ICPM 2023 - 2nd International Workshop on Education meets Process Mining at the 5th International Conference on Process Mining. Rome, Italy, Oct 23-27, 2023. DOI

[206]

C. Leiber • L. Miklautz • C. Plant • C. Böhm
Application of Deep Clustering Algorithms.
CIKM 2023 - 32nd ACM International Conference on Information and Knowledge Management. Birmingham, UK, Oct 21-25, 2023. DOI

[205]

J. Hanselle • J. Fürnkranz • E. Hüllermeier
Probabilistic Scoring Lists for Interpretable Machine Learning.
DS 2023 - 26th International Conference on Discovery Science. Porto, Portugal, Oct 09-11, 2023. DOI

[204]

L. Miklautz • A. Shkabrii • C. Leiber • B. Tobias • B. Seidl • E. Weissensteiner • A. Rausch • C. Böhm • C. Plant
Non-Redundant Image Clustering of Early Medieval Glass Beads.
DSAA 2023 - 10th IEEE International Conference on Data Science and Advanced Analytics. Thessaloniki, Greece, Oct 09-13, 2023. DOI

[203]

J. Brandt • E. Schede • S. Sharma • V. Bengs • E. Hüllermeier • K. Tierney
Contextual Preselection Methods in Pool-based Realtime Algorithm Configuration.
LWDA 2023 - Conference on Lernen. Wissen. Daten. Analysen. Marburg, Germany, Oct 09-11, 2023. PDF

[202]

J. Hanselle • J. Kornowicz • S. Heid • K. Thommes • E. Hüllermeier
Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain.
LWDA 2023 - Conference on Lernen. Wissen. Daten. Analysen. Marburg, Germany, Oct 09-11, 2023. PDF

[201]

M. Bernhard • N. Strauß • M. Schubert
MapFormer: Boosting Change Detection by Using Pre-change Information.
ICCV 2023 - IEEE/CVF International Conference on Computer Vision. Paris, France, Oct 02-06, 2023. DOI GitHub

[200]

H. Chen • A. Frikha • D. Krompass • J. Gu • V. Tresp
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation.
ICCV 2023 - IEEE/CVF International Conference on Computer Vision. Paris, France, Oct 02-06, 2023. DOI

[199]

H. Li • J. Gu • R. Koner • S. Sharifzadeh • V. Tresp
Do DALL-E and Flamingo Understand Each Other?
ICCV 2023 - IEEE/CVF International Conference on Computer Vision. Paris, France, Oct 02-06, 2023. DOI GitHub

[198]

G. Zhang • J. Ren • J. Gu • V. Tresp
Multi-event Video-Text Retrieval.
ICCV 2023 - IEEE/CVF International Conference on Computer Vision. Paris, France, Oct 02-06, 2023. DOI GitHub

[197]

Y. Shen • R. Liao • Z. Han • Y. Ma • V. Tresp
GraphextQA: A Benchmark for Evaluating Graph-Enhanced Large Language Models.
Preprint (Oct. 2023). arXiv

[196]

D. Winkel • N. Strauß • M. Schubert • T. Seidl
Simplex Decomposition for Portfolio Allocation Constraints in Reinforcement Learning.
ECAI 2023 - 26th European Conference on Artificial Intelligence. Kraków, Poland, Sep 30-Oct 04, 2023. DOI

[195]

P. Becker • V. Bengs
Shapley-Based Feature Selection for Online Algorithm Selection.
DynXAI @ECML-PKDD 2023 - Workshop on Explainable Artificial Intelligence: From Static to Dynamic at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[194]

Z. Ding • J. Wu • Z. Li • Y. Ma • V. Tresp
Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs Using Confidence-Augmented Reinforcement Learning.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI GitHub

[193]

S. Gilhuber • J. Busch • D. Rotthues • C. M. M. Frey • T. Seidl
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[192]

S. Gilhuber • R. Hvingelby • M. L. A. Fok • T. Seidl
How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[191]

S. Haas • E. Hüllermeier
Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[190]

M. Klein • C. Leiber • C. Böhm
k-SubMix: Common Subspace Clustering on Mixed-Type Data.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[189]

M. Muschalik • F. Fumagalli • B. Hammer • E. Hüllermeier
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams.
ECML-PKDD 2023 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[188]

[187]

T. Kaufmann • S. Ball • J. Beck • E. Hüllermeier • F. Kreuter
On the challenges and practices of reinforcement learning from real human feedback.
HLDM @ECML-PKDD 2023 - 1st Workshop on Hybrid Human-Machine Learning and Decision Making at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[186]

E. Terzieva • M. Muschalik • P. Hofman • E. Hüllermeier
Identifying Trends in Feature Attributions During Training of Neural Networks.
Uncertainty meets Explainability @ECML-PKDD 2023 - Workshop Uncertainty meets Explainability in Machine Learning at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Turin, Italy, Sep 18-22, 2023. DOI

[185]

A. Javanmardi • Y. Sale • P. Hofman • E. Hüllermeier
Conformal Prediction with Partially Labeled Data.
COPA 2023 - 12th Symposium on Conformal and Probabilistic Prediction with Applications. Limassol, Cyprus, Sep 13-15, 2023. URL

[184]

L. Rottkamp • N. Strauß • M. Schubert
DEAR: Dynamic Electric Ambulance Redeployment.
SSTD 2023 - 18th International Symposium on Spatial and Temporal Databases. Calgary, Canada, Aug 23-25, 2023. DOI

[183]

Z. Liu • Y. Ma • H. Li • M. Hildebrandt • Y. Ouyang • Z. Xiong
Debiased Contrastive Loss for Collaborative Filtering.
KSEM 2024 - 16th International Conference Knowledge Science, Engineering and Management. Guangzhou, China, Aug 16-18, 2023. DOI

[182]

A. Beer • A. Draganov • E. Hohma • P. Jahn • C. M. M. Frey • I. Assent
Connecting the Dots — Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering.
KDD 2023 - 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Long Beach, CA, USA, Aug 06-10, 2023. DOI GitHub

[181]

M. Caprio • Y. Sale • E. Hüllermeier • I. Lee
A Novel Bayes' Theorem for Upper Probabilities.
Epi UAI 2023 - International Workshop on Epistemic Uncertainty in Artificial Intelligence. Pittsburgh, PA, USA, Aug 04, 2023. DOI

[180]

S. Henzgen • E. Hüllermeier
Weighting by Tying: A New Approach to Weighted Rank Correlation.
Preprint (Aug. 2023). arXiv

[179]

Y. Sale • M. Caprio • E. Hüllermeier
Is the Volume of a Credal Set a Good Measure for Epistemic Uncertainty?
UAI 2023 - 39th Conference on Uncertainty in Artificial Intelligence. Pittsburgh, PA, USA, Jul 31-Aug 03, 2023. URL

[178]

[177]

M. K. Belaid • R. Bornemann • M. Rabus • R. Krestel • E. Hüllermeier
Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark.
xAI 2023 - 1st World Conference on eXplainable Artificial Intelligence. Lisbon, Portugal, Jul 26-28, 2023. DOI GitHub

[176]

M. Muschalik • F. Fumagalli • R. Jagtani • B. Hammer • E. Hüllermeier
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios.
xAI 2023 - 1st World Conference on eXplainable Artificial Intelligence. Lisbon, Portugal, Jul 26-28, 2023. Best Paper Award. DOI

[175]

V. Bengs • E. Hüllermeier • W. Waegeman
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[174]

M. Biloš • K. Rasul • A. Schneider • Y. Nevmyvaka • S. Günnemann
Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[173]

T. Wollschläger • N. Gao • B. Charpentier • M. A. Ketata • S. Günnemann
Uncertainty Estimation for Molecules: Desiderata and Methods.
ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL

[172]

A. Giovagnoli • Y. Ma • M. Schubert • V. Tresp
QNEAT: Natural Evolution of Variational Quantum Circuit Architecture.
GECCO 2023 - Genetic and Evolutionary Computation Conference. Lisbon, Portugal, Jul 15-19, 2023. DOI

[171]

M. Wever • M. Özdogan • E. Hüllermeier
Cooperative Co-Evolution for Ensembles of Nested Dichotomies for Multi-Class Classification.
GECCO 2023 - Genetic and Evolutionary Computation Conference. Lisbon, Portugal, Jul 15-19, 2023. DOI

[170]

M. Fromm • M. Berrendorf • E. Faerman • T. Seidl
Cross-Domain Argument Quality Estimation.
Findings @ACL 2023 - Findings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada, Jul 09-14, 2023. DOI

[169]

Z. Han • R. Liao • J. Gu • Y. Zhang • Z. Ding • Y. Gu • H. Köppl • H. Schütze • V. Tresp
ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations.
Findings @ACL 2023 - Findings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada, Jul 09-14, 2023. DOI

[168]

J. Gu • Z. Han • S. Chen • A. Beirami • B. He • G. Zhang • R. Liao • Y. Qin • V. Tresp • P. Torr
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models.
Preprint (Jul. 2023). arXiv

[167]

C. M. M. Frey
Learning from complex networks.
Dissertation LMU München. Jun. 2023. DOI

[166]

T. Tornede • A. Tornede • J. Hanselle • F. Mohr • M. Wever • E. Hüllermeier
Towards Green Automated Machine Learning: Status Quo and Future Directions.
Journal of Artificial Intelligence Research 77. Jun. 2023. DOI

[165]

M. Lotfollahi • A. K. Susmelj • C. De Donno • L. Hetzel • Y. Ji • I. L. Ibarra • S. R. Srivatsan • M. Naghipourfar • R. M. Daza • B. Martin • J. Shendure • J. L. McFaline‐Figueroa • P. Boyeau • F. A. Wolf • N. Yakubova • S. Günnemann • C. Trapnell • D. Lopez‐Paz • F. J. Theis
Predicting cellular responses to complex perturbations in high-throughput screens.
Molecular Systems Biology 19.e11517. Jun. 2023. DOI

[164]

J. Sommer • L. Hetzel • D. Lüdke • F. J. Theis • S. Günnemann
The power of motifs as inductive bias for learning molecular distributions.
Preprint (Jun. 2023). arXiv

[163]

D. Winkel • N. Strauß • M. Schubert • Y. Ma • T. Seidl
Constrained Portfolio Management using Action Space Decomposition for Reinforcement Learning.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI

[162]

A.-K. Wickert • C. Damke • L. Baumgärtner • E. Hüllermeier • M. Mezini
UnGoML: Automated Classification of unsafe Usages in Go.
MSR 2023 - IEEE/ACM 20th International Conference on Mining Software Repositories. Melbourne, Australia, May 15-16, 2023. FOSS (Free, Open Source Software) Impact Paper Award. DOI GitHub

[161]

[160]

Z. Liu • Y. Ma • M. Schubert • Y. Ouyang • W. Rong • Z. Xiong
Multimodal Contrastive Transformer for Explainable Recommendation.
IEEE Transactions on Computational Social Systems. May. 2023. DOI

[159]

L. G. M. Bauer • C. Leiber • C. Böhm • C. Plant
Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering.
SDM 2023 - SIAM International Conference on Data Mining. Minneapolis, MN, USA, Apr 27-29, 2023. DOI

[158]

D. Schubert • P. Gupta • M. Wever
Meta-learning for Automated Selection of Anomaly Detectors for Semi-supervised Datasets.
IDA 2023 - 21st International Symposium on Intelligent Data Analysis. Louvain-la-Neuve, Belgium, Apr 12-14, 2023. DOI

[157]

T. Tornede • A. Tornede • L. Fehring • L. Gehring • H. Graf • J. Hanselle • F. Mohr • M. Wever
PyExperimenter: Easily distribute experiments and track results.
The Journal of Open Source Software 8.86. Apr. 2023. DOI

[156]

M. K. Belaid • D. E. Mekki • M. Rabus • E. Hüllermeier
Optimizing Data Shapley Interaction Calculation from $O(2^n)$ to $O(t n^2)$ for KNN models.
Preprint (Apr. 2023). arXiv

[155]

E. Hüllermeier
Representation of Quantification of Uncertainty in Machine Learning.
TRR 165/181 2023 - Scale interactions, data-driven modeling, and uncertainty in weather and climate. Ingolstadt, Germany, Mar 27-30, 2023. Invited Talk. PDF

[154]

[153]

J. Brandt • E. Schede • B. Haddenhorst • V. Bengs • E. Hüllermeier • K. Tierney
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration.
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI

[152]

R. Koner • T. Hannan • S. Shit • S. Sharifzadeh • M. Schubert • T. Seidl • V. Tresp
InstanceFormer: An Online Video Instance Segmentation Framework.
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI GitHub

[151]

J. Brandt • M. Wever • D. Iliadis • V. Bengs • E. Hüllermeier
Iterative Deepening Hyperband.
Preprint (Feb. 2023). arXiv

[150]

V. Bengs • E. Hüllermeier
Multi-armed bandits with censored consumption of resources.
Machine Learning 112.1. Jan. 2023. DOI

[149]

P. Gupta • J. P. Drees • E. Hüllermeier
Automated Side-Channel Attacks using Black-Box Neural Architecture Search.
Preprint (Jan. 2023). URL

[148]

O. Shchur
Modeling Continuous-time Event Data with Neural Temporal Point Processes.
Dissertation TU München. Dec. 2022. URL

[147]

S. Legler • T. Janjic • M. H. Shaker • E. Hüllermeier
Machine learning for estimating parameters of a convective-scale model: A comparison of neural networks and random forests.
Computational Intelligence 2022 - 32nd Workshop on Computational Intelligence of the VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik. Berlin, Germany, Dec 01-02, 2022. PDF

[146]

M. Ali • M. Berrendorf • C. T. Hoyt • L. Vermue • M. Galkin • S. Sharifzadeh • A. Fischer • V. Tresp • J. Lehmann
Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models under a Unified Framework.
IEEE Transactions on Pattern Analysis and Machine Intelligence 44.12. Dec. 2022. DOI GitHub

[145]

W. Durani • D. Mautz • C. Plant • C. Böhm
DBHD: Density-based clustering for highly varying density.
ICDM 2022 - 22nd IEEE International Conference on Data Mining. Orlando, FL, USA, Nov 30-Dec 02, 2022. DOI

[144]

S. Gilhuber • P. Jahn • Y. Ma • T. Seidl
VERIPS: Verified Pseudo-label Selection for Deep Active Learning.
ICDM 2022 - 22nd IEEE International Conference on Data Mining. Orlando, FL, USA, Nov 30-Dec 02, 2022. DOI GitHub

[143]

N. Strauß • M. Berrendorf • T. Haider • M. Schubert
A Comparison of Ambulance Redeployment Systems on Real-World Data.
Workshop @ICDM 2022 - Workshop at the 22nd IEEE International Conference on Data Mining. Orlando, FL, USA, Nov 30-Dec 02, 2022. DOI GitHub

[142]

H. Aliee • T. Richter • M. Solonin • I. Ibarra • F. J. Theis • N. Kilbertus
Sparsity in Continuous-Depth Neural Networks.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[141]

V. Bengs • E. Hüllermeier • W. Waegeman
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[140]

J. Brandt • V. Bengs • B. Haddenhorst • E. Hüllermeier
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[139]

L. Hetzel • S. Boehm • N. Kilbertus • S. Günnemann • M. Lotfollahi • F. J. Theis
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[138]

Y. Scholten • J. Schuchardt • S. Geisler • A. Bojchevski • S. Günnemann
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks.
NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. DOI

[137]

A. Campagner • J. Lienen • E. Hüllermeier • D. Ciucci
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning.
IJCRS 2022 - International Joint Conference on Rough Sets. Suzhou, China, Nov 11-14, 2022. DOI

[136]

A. Frikha
Deep knowledge transfer for generalization across tasks and domains under data scarcity: on intersections of anomaly detection, few-shot learning, continual learning, domain generalization and data-free learning.
Dissertation LMU München. Nov. 2022. DOI

[135]

M. Bernhard • M. Schubert
Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse Geo-Annotations.
ACM SIGSPATIAL 2022 - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI GitHub

[134]

[133]

A. Lohrer • J. J. Binder • P. Kröger
Group Anomaly Detection for Spatio-Temporal Collective Behaviour Scenarios in Smart Cities.
IWCTS @ACM SIGSPATIAL 2022 - 15th International Workshop on Computational Transportation Science at the 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI

[132]

S. Shit • R. Koner • B. Wittmann • J. C. Paetzold • I. Ezhov • H. Li • J. Pan • S. Sharifzadeh • G. Kaissis • V. Tresp • B. Menze
Relationformer: A Unified Framework for Image-to-Graph Generation.
ECCV 2022 - 17th European Conference on Computer Vision. Tel Aviv, Israel, Oct 23-27, 2022. DOI GitHub

[131]

C. Zelenka • A. Lohrer • M. Bayer • P. Kröger
AI4EO Hyperview: A SpectralNet3D and RNNPlus Approach for Sustainable Soil Parameter Estimation on Hyperspectral Image Data.
ICIP 2022 - IEEE International Conference on Image Processing. Bordeaux, France, Oct 16-19, 2022. DOI

[130]

E. Schede • J. Brandt • A. Tornede • M. Wever • V. Bengs • E. Hüllermeier • K. Tierney
A Survey of Methods for Automated Algorithm Configuration.
Journal of Artificial Intelligence Research 75. Oct. 2022. DOI

[129]

C. M. M. Frey • Y. Ma • M. Schubert
SEA: Graph Shell Attention in Graph Neural Networks.
ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

[128]

N. Strauß • D. Winkel • M. Berrendorf • M. Schubert
Reinforcement Learning for Multi-Agent Stochastic Resource Collection.
ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

[127]

D. Winkel • N. Strauß • M. Schubert • T. Seidl
Risk-Aware Reinforcement Learning for Multi-Period Portfolio Selection.
ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

[126]

S. Gilhuber • M. Berrendorf • Y. Ma • T. Seidl
Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations.
IAL @ECML-PKDD 2022 - 6th International Workshop on Interactive Adaptive Learning at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. PDF GitHub

[125]

E. Hohma • C. M. M. Frey • A. Beer • T. Seidl
SCAR - Spectral Clustering Accelerated and Robustified.
VLDB 2022 - 48th International Conference on Very Large Data Bases. Sydney, Australia (and hybrid), Sep 05-09, 2022. DOI GitHub

[124]

C. Leiber • L. G. M. Bauer • M. Neumayr • C. Plant • C. Böhm
The DipEncoder: Enforcing Multimodality in Autoencoders.
KDD 2022 - 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Washington, DC, USA, Aug 14-18, 2022. DOI

[123]

Z. Ding • Z. Li • R. Qi • J. Wu • B. He • Y. Ma • Z. Meng • S. Chen • R. Liao • Z. Han • V. Tresp
Forecasting Question Answering over Temporal Knowledge Graphs.
Preprint (Aug. 2022). arXiv

[122]

M. Fromm
Machine learning driven argument mining.
Dissertation LMU München. Jul. 2022. DOI

[121]

E. Schede • J. Brandt • A. Tornede • M. Wever • V. Bengs • E. Hüllermeier • K. Tierney
A Survey of Methods for Automated Algorithm Configuration.
IJCAI-ECAI 2022 - 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. Extended Abstract. DOI

[120]

M. Ali • M. Berrendorf • M. Galkin • V. Thost • T. Ma • V. Tresp • J. Lehmann
Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract).
IJCAI-ECAI 2022 - Best paper track at the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. DOI

[119]

L. Hetzel • S. Boehm • N. Kilbertus • S. Günnemann • M. Lotfollahi • F. J. Theis
Predicting single-cell perturbation responses for unseen drugs.
MLDD @ICML 2022 - Workshop on Machine Learning for Drug Discovery at the 39th International Conference on Machine Learning. Baltimore, MD, USA, Jul 17-23, 2022. URL

[118]

H. Li • Q. Khan • V. Tresp • D. Cremers
Biologically Inspired Neural Path Finding.
BI 2022 - 15th International Conference on Brain Informatics. Padova, Italy, Jul 15-15, 2022. DOI GitHub

[117]

Z. Liu • Y. Ma • M. Hildebrandt • Y. Ouyang • Z. Xiong
CDARL: a contrastive discriminator-augmented reinforcement learning framework for sequential recommendations.
Knowledge and Information Systems 64. Jul. 2022. DOI

[116]

Z. Liu • Y. Ma • M. Schubert • Y. Ouyang • Z. Xiong
Multi-Modal Contrastive Pre-training for Recommendation.
ICMR 2022 - ACM International Conference on Multimedia Retrieval. Newark, NJ, USA, Jun 27-30, 2022. DOI

[115]

G. Fu • Z. Meng • Z. Han • Z. Ding • Y. Ma • M. Schubert • V. Tresp • R. Wattenhofer
TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion.
SPNLP @ACL 2022 - 6th ACL Workshop on Structured Prediction for NLP at the 60th Annual Meeting of the Association for Computational Linguistics. Dublin, Ireland, May 22-27, 2022. DOI

[114]

D. Zügner
Adversarial Robustness of Graph Neural Networks.
Dissertation TU München. May. 2022. URL

[113]

C. Leiber • D. Mautz • C. Plant • C. Böhm
Automatic Parameter Selection for Non-Redundant Clustering.
SDM 2022 - SIAM International Conference on Data Mining. Virtual, Apr 28-30, 2022. DOI

[112]

D. Alivanistos • M. Berrendorf • M. Cochez • M. Galkin
Query Embedding on Hyper-Relational Knowledge Graphs.
ICLR 2022 - 10th International Conference on Learning Representations. Virtual, Apr 25-29, 2022. URL GitHub

[111]

M. Galkin • M. Berrendorf • C. T. Hoyt
An Open Challenge for Inductive Link Prediction on Knowledge Graphs.
GLB @WWW 2022 - Workshop on Graph Learning Benchmarks at the International World Wide Web Conference. Virtual, Apr 22-29, 2022. arXiv GitHub

[110]

C. T. Hoyt • M. Berrendorf • M. Gaklin • V. Tresp • B. M. Gyori
A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphs.
GLB @WWW 2022 - Workshop on Graph Learning Benchmarks at the International World Wide Web Conference. Virtual, Apr 22-29, 2022. arXiv

[109]

D. Kazempour
Advances in correlation clustering.
Dissertation LMU München. Mar. 2022. DOI

[108]

Y. Liu • Y. Ma • M. Hildebrandt • M. Joblin • V. Tresp
TLogic: Temporal logical rules for explainable link forecasting on temporal knowledge graphs.
AAAI 2022 - 36th Conference on Artificial Intelligence. Virtual, Feb 22-Mar 01, 2022. DOI

[107]

S. Sharifzadeh • S. M. Baharlou • M. Schmitt • H. Schütze • V. Tresp
Improving Scene Graph Classification by Exploiting Knowledge from Texts.
AAAI 2022 - 36th Conference on Artificial Intelligence. Virtual, Feb 22-Mar 01, 2022. DOI

[106]

M. Berrendorf
Machine learning for managing structured and semi-structured data.
Dissertation LMU München. Jan. 2022. DOI

[105]

V.-L. Nguyen • M. H. Shaker • E. Hüllermeier
How to measure uncertainty in uncertainty sampling for active learning.
Machine Learning 111.1. Jan. 2022. DOI

[104]

L. Qian • C. Plant • C. Böhm
Density-based Clustering for Adaptive Density Variation.
ICDM 2021 - 21st IEEE International Conference on Data Mining. Auckland, New Zealand, Dec 07-10, 2021. DOI

[103]

A. Beer • L. Stephan • T. Seidl
LUCKe- Connecting Clustering and Correlation Clustering.
Workshop @ICDM 2021 - Workshop at the 21st IEEE International Conference on Data Mining. Auckland, New Zealand, Dec 07-10, 2021. DOI

[102]

J. Busch • M. Hünemörder • J. Held • P. Kröger • T. Seidl
Implicit Hough Transform Neural Networks for Subspace Clustering.
Workshop @ICDM 2021 - Workshop at the 21st IEEE International Conference on Data Mining. Auckland, New Zealand, Dec 07-10, 2021. DOI

[101]

A. Lohrer • J. Deller • M. Hünemörder • P. Kröger
OAB - An Open Anomaly Benchmark Framework for Unsupervised and Semisupervised Anomaly Detection on Image and Tabular Data Sets.
Workshop @ICDM 2021 - Workshop at the 21st IEEE International Conference on Data Mining. Auckland, New Zealand, Dec 07-10, 2021. DOI

[100]

L. Hetzel • D. S. Fischer • S. Günnemann • F. J. Theis
Graph representation learning for single-cell biology.
Current Opinion in Systems Biology 28.100347. Dec. 2021. DOI

[99]

M. Bernhard • M. Schubert
Correcting Imprecise Object Locations for Training Object Detectors in Remote Sensing Applications.
Remote Sensing 13. Dec. 2021. URL

[98]

A. Beer
On the edges of clustering: creating synergies with related problems.
Dissertation LMU München. Nov. 2021. DOI

[97]

N. Kees • M. Fromm • E. Faerman • T. Seidl
Active Learning for Argument Strength Estimation.
Insights @EMNLP 2021 - 2nd Workshop on Insights from Negative Results at the Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic, Nov 07-11, 2021. DOI

[96]

M. Ali • M. Berrendorf • M. Galkin • V. Thost • T. Ma • V. Tresp • J. Lehmann
Improving Inductive Link Prediction Using Hyper-Relational Facts.
ISWC 2021 - 20th International Semantic Web Conference. Virtual, Oct 24-28, 2021. Best Paper Award. DOI GitHub

[95]

D. Kazempour • A. Beer • M. Oelker • P. Kröger • T. Seidl
Compound Segmentation via Clustering on Mol2Vec-based Embeddings.
eScience 2021 - 17th IEEE eScience Conference. Virtual, Sep 20-23, 2021. DOI

[94]

S. Gilhuber • A. Beer • F. Wahl • T. Seidl
Cluster Flow — an Advanced Concept for Ensemble-Enabling, Interactive Clustering.
BTW 2021 - 19th Symposium of Database Systems for Business, Technology and Web. Dresden, Germany, Sep 13-17, 2021. DOI

[93]

D. Kazempour • J. Winter • P. Kröger • T. Seidl
On Methods and Measures for the Inspection of Arbitrarily Oriented Subspace Clusters.
Datenbank-Spektrum 21. Sep. 2021. DOI

[92]

T. Seidl • M. Fromm • S. Gilhuber
Proceedings of the LWDA 2021 Workshops: FGWM, KDML, FGWI-BIA, and FGIR.
LWDA 2021 - Lernen, Wissen, Daten, Analysen 2021. Sep. 2021. URL

[91]

A. Lohrer • A. Beer • M. Hünemörder • J. Lauterbach • T. Seidl • P. Kröger
AnyCORE - An Anytime Algorithm for Cluster Outlier REmoval.
LWDA 2021 - Conference on Lernen. Wissen. Daten. Analysen. München, Germany, Sep 01-03, 2021. PDF

[90]

L. Miklautz • L. G. M. Bauer • D. Mautz • S. Tschiatschek • C. Böhm • C. Plant
Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces.
IJCAI 2021 - 30th International Joint Conference on Artificial Intelligence. Montreal, Canada, Aug 19-26, 2021. DOI

[89]

C. Leiber • L. G. M. Bauer • B. Schelling • C. Böhm • C. Plant
Dip-based Deep Embedded Clustering with k-Estimation.
KDD 2021 - 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Singapore, Aug 14-18, 2021. DOI

[88]

M. Biloš • S. Günnemann
Scalable Normalizing Flows for Permutation Invariant Densities.
ICML 2021 - 38th International Conference on Machine Learning. Virtual, Jul 18-24, 2021. URL

[87]

N. Strauß • L. Rottkamp • S. Schmoll • M. Schubert
Efficient Parking Search using Shared Fleet Data.
MDM 2021 - 22nd IEEE International Conference on Mobile Data Management. Virtual, Jun 15-18, 2021. DOI

[86]

J. Schuchardt • A. Bojchevski • J. Gasteiger • S. Günnemann
Collective Robustness Certificates - Exploiting Interdependence in Graph Neural Networks.
ICLR 2021 - 9th International Conference on Learning Representations. Virtual, May 03-07, 2021. URL

[85]

E. Faerman
Representation learning on relational data.
Dissertation LMU München. Apr. 2021. DOI

[84]

Y. Ma • V. Tresp
Causal Inference under Networked Interference and Intervention Policy Enhancement.
AISTATS 2021 - 24th International Conference on Artificial Intelligence and Statistics. Virtual, Apr 13-15, 2021. URL

[83]

M. Berrendorf • E. Faerman • V. Tresp
Active Learning for Entity Alignment.
ECIR 2021 - 43rd European Conference on Information Retrieval. Virtual, Mar 28-Apr 01, 2021. DOI GitHub

[82]

M. Berrendorf • L. Wacker • E. Faerman
A Critical Assessment of State-of-the-Art in Entity Alignment.
ECIR 2021 - 43rd European Conference on Information Retrieval. Virtual, Mar 28-Apr 01, 2021. DOI GitHub

[81]

M. Fromm • M. Berrendorf • S. Gilhuber • T. Seidl • E. Faerman
Diversity Aware Relevance Learning for Argument Search.
ECIR 2021 - 43rd European Conference on Information Retrieval. Virtual, Mar 28-Apr 01, 2021. DOI GitHub

[80]

A. Beer • E. Allerborn • V. Hartmann • T. Seidl
KISS - A fast kNN-based Importance Score for Subspaces.
EDBT 2021 - 24th International Conference on Extending Database Technology. Nicosia, Cyprus, Mar 23-26, 2021. PDF

[79]

M. Ali • M. Berrendorf • C. T. Hoyt • L. Vermue • S. Sharifzadeh • V. Tresp • J. Lehmann
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings.
Journal of Machine Learning Research 22.82. Mar. 2021. PDF

[78]

M. Fromm • E. Faerman • M. Berrendorf • S. Bhargava • R. Qi • Y. Zhang • L. Dennert • S. Selle • Y. Mao • T. Seidl
Argument Mining Driven Analysis of Peer-Reviews.
AAAI 2021 - 35th Conference on Artificial Intelligence. Virtual, Feb 02-09, 2021. DOI GitHub

[77]

S. Sharifzadeh • S. M. Baharlou • V. Tresp
Classification by Attention: Scene Graph Classification with Prior Knowledge.
AAAI 2021 - 35th Conference on Artificial Intelligence. Virtual, Feb 02-09, 2021. DOI

[76]

S. Schmoll • M. Schubert
Semi-Markov Reinforcement Learning for Stochastic Resource Collection.
IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence. Yokohama, Japan (postponed due to the Corona pandemic), Jan 07-15, 2021. DOI

[75]

M. Berrendorf • E. Faerman • L. Vermue • V. Tresp
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank.
WI-IAT 2020 - IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. Virtual, Dec 14-17, 2020. DOI

[74]

E. Faerman • F. Borutta • J. Busch • M. Schubert
Ada-LLD: Adaptive Node Similarity Using Multi-Scale Local Label Distributions.
WI-IAT 2020 - IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. Virtual, Dec 14-17, 2020. DOI GitHub

[73]

S. Gilhuber • M. Berrendorf • P. Kröger
Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation.
WI-IAT 2020 - IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology. Virtual, Dec 14-17, 2020. DOI

[72]

C. Böhm • C. Plant
Massively Parallel Graph Drawing and Representation Learning.
IEEE BigData 2020 - IEEE International Conference on Big Data. Virtual, Dec 10-13, 2020. DOI

[71]

C. Böhm • C. Plant
Massively Parallel Random Number Generation.
IEEE BigData 2020 - IEEE International Conference on Big Data. Virtual, Dec 10-13, 2020. DOI

[70]

M. Perdacher • C. Plant • C. Böhm
Improved Data Locality Using Morton-order Curve on the Example of LU Decomposition.
IEEE BigData 2020 - IEEE International Conference on Big Data. Virtual, Dec 10-13, 2020. DOI

[69]

S. Geisler • D. Zügner • S. Günnemann
Reliable Graph Neural Networks via Robust Aggregation.
NeurIPS 2020 - 34th Conference on Neural Information Processing Systems. Virtual, Dec 06-12, 2020. URL

[68]

O. Shchur • N. Gao • M. Biloš • S. Günnemann
Fast and Flexible Temporal Point Processes with Triangular Maps.
NeurIPS 2020 - 34th Conference on Neural Information Processing Systems. Virtual, Dec 06-12, 2020. URL

[67]

Y. Ma • V. Tresp
A Variational Quantum Circuit Model for Knowledge Graph Embeddings.
QTNML @NeurIPS 2020 - 1st Workshop on Quantum Tensor Networks in Machine Learning at the 34th Conference on Neural Information Processing Systems. Virtual, Dec 06-12, 2020. PDF

[66]

J. Busch • E. Faerman • M. Schubert • T. Seidl
Learning Self-Expression Metrics for Scalable and Inductive Subspace Clustering.
SSL @NeurIPS 2020 - Workshop on Self-Supervised Learning - Theory and Practice at the 34th Conference on Neural Information Processing Systems. Virtual, Dec 06-12, 2020. arXiv GitHub

[65]

M. Berrendorf • E. Faerman
mberr/ea-active-learning: Zenodo. Version 1.0.1.
2020. DOI

[64]

M. Berrendorf • L. Wacker • E. Faerman
mberr/ea-sota-comparison: Zenodo. Version v1.1.1.
2020. DOI

[63]

Y. Zhang • Y. Lu • T. Seidl
KNNAC: An Efficient k Nearest Neighbor Based Clustering with Active Core Detection.
iiWAS 2020 - 22nd International Conference on Information Integration and Web-based Applications and Services. Chiang Mai, Thailand, Nov 30-Dec 02, 2020. DOI

[62]

J. Brandt • E. Schede • V. Bengs • B. Haddenhorst • K. Tierney • E. Hüllermeier
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Applications in Algorithm Configuration.
DA2PL 2020 - Wokshop From Multiple Criteria Decision Aid to Preference Learning. Compiègne, France, Nov 17-18, 2020. PDF

[61]

D. Kazempour • A. Beer • P. Kröger • T. Seidl
I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering through piecewise-linear approximations of manifolds.
Workshop @ICDM 2020 - Workshop at the 20th IEEE International Conference on Data Mining. Sorrento, Italy, Nov 17-20, 2020. DOI

[60]

D. Kazempour • P. Kröger • T. Seidl
Towards an Internal Evaluation Measure for Arbitrarily Oriented Subspace Clustering.
Workshop @ICDM 2020 - Workshop at the 20th IEEE International Conference on Data Mining. Sorrento, Italy, Nov 17-20, 2020. DOI

[59]

D. Kazempour • L. M. Yan • P. Kröger • T. Seidl
You see a set of wagons - I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters.
Workshop @ICDM 2020 - Workshop at the 20th IEEE International Conference on Data Mining. Sorrento, Italy, Nov 17-20, 2020. DOI

[58]

[57]

Y. Ma • Z. Han • V. Tresp
Learning with Temporal Knowledge Graphs.
Workshop @CIKM 2020 - Workshop at the 29th ACM International Conference on Information and Knowledge Management. Galway, Ireland, Oct 19-23, 2020. Invited Talk. PDF

[56]

T. Seidl
Keynote: Data Mining on Process Data.
ICPM 2020 - 2nd International Conference on Process Mining. Virtual, Oct 04-09, 2020. DOI

[55]

A. Maldonado • J. Sontheim • F. Richter • T. Seidl
Performance Skyline: Inferring Process Performance Models from Interval Events.
SA4PM @ICPM 2020 - 1st International Workshop on Streaming Analytics for Process Mining at the 2nd International Conference on Process Mining. Virtual, Oct 04-09, 2020. DOI

[54]

A. Beer • D. Seeholzer • N. S. Schüler • T. Seidl
Angle-Based Clustering.
SISAP 2020 - 13th International Conference on Similarity Search and Applications. Virtual, Sep 30-Oct 02, 2020. DOI

[53]

Y. Ma
Learning with relational knowledge in the context of cognition, quantum computing, and causality.
Dissertation LMU München. Sep. 2020. DOI

[52]

A. Beer • D. Kazempour • J. Busch • A. Tekles • T. Seidl
Grace - Limiting the Number of Grid Cells for Clustering High-Dimensional Data.
LWDA 2020 - Conference on Lernen. Wissen. Daten. Analysen. Bonn, Germany, Sep 09-11, 2020. PDF

[51]

C. Plant • S. Biedermann • C. Böhm
Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI

[50]

D. Zügner • S. Günnemann
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbation.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI

[49]

C. Böhm
Space-filling Curves for High-performance Data Mining.
Preprint (Aug. 2020). arXiv

[48]

A. Beer • V. Hartmann • T. Seidl
Orderings of Data - more than a Tripping Hazard.
SSDBM 2020 - 32nd International Conference on Scientific and Statistical Database Management. Vienna, Austria, Jul 07-09, 2020. DOI

[47]

D. Mautz • C. Plant • C. Böhm
DeepECT: The Deep Embedded Cluster Tree.
Data Science and Engineering 5. Jul. 2020. DOI

[46]

S. Friedl • S. Schmoll • F. Borutta • M. Schubert
SMART-Env.
MDM 2020 - 21st IEEE International Conference on Mobile Data Management. Versailles, France, Jun 30-Jul 03, 2020. DOI

[45]

M. Ali • C. T. Hoyt • L. Vermue • M. Galkin • M. Berrendorf
pykeen/benchmarking. Version v1.0.
2020. DOI

[44]

D. Mautz • W. Ye • C. Plant • C. Böhm
Non-Redundant Subspace Clusterings with Nr-Kmeans and Nr-DipMeans.
ACM Transactions on Knowledge Discovery from Data 14.5. Jun. 2020. DOI

[43]

F. Borutta • D. Kazempour • F. Marty • P. Kröger • T. Seidl
Detecting Arbitrarily Oriented Subspace Clusters in Data Streams Using Hough Transform.
PAKDD 2020 - 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Singapore, May 11-14, 2020. DOI

[42]

J. Klicpera • J. Groß • S. Günnemann
Directional Message Passing for Molecular Graphs.
ICLR 2020 - 8th International Conference on Learning Representations. Virtual, Apr 26-May 01, 2020. URL

[41]

O. Shchur • M. Biloš • S. Günnemann
Intensity-Free Learning of Temporal Point Processes.
ICLR 2020 - 8th International Conference on Learning Representations. Virtual, Apr 26-May 01, 2020. Spotlight Presentation. URL

[40]

M. Berrendorf • E. Faerman • V. Tresp
Active Learning for Entity Alignment.
DL4G @WWW 2020 - 5th International Workshop on Deep Learning for Graphs at the International World Wide Web Conference. Taipeh, Taiwan, Apr 21, 2020. arXiv

[39]

M. Berrendorf • E. Faerman • L. Vermue • V. Tresp
Interpretable and Fair Comparison of Link Prediction or Entity Alignment Methods with Adjusted Mean Rank (Extended Abstract).
DL4G @WWW 2020 - 5th International Workshop on Deep Learning for Graphs at the International World Wide Web Conference. Taipeh, Taiwan, Apr 21, 2020. Full paper at WI-AT 2020. DOI

[38]

M. C. Altinigneli • L. Miklautz • C. Böhm • C. Plant
Hierarchical Quick Shift Guided Recurrent Clustering.
ICDE 2020 - 36th IEEE International Conference on Data Engineering. Dallas, TX, USA, Apr 20-24, 2020. DOI

[37]

[36]

F. Borutta
Unsupervised learning on social data.
Dissertation LMU München. Mar. 2020. DOI

[35]

L. Miklautz • D. Mautz • M. C. Altinigneli • C. Böhm • C. Plant
Deep embedded non-redundant clustering.
AAAI 2020 - 34th Conference on Artificial Intelligence. New York City, New York, USA, Feb 07-12, 2020. DOI

[34]

[33]

E. Faerman • O. Voggenreiter • F. Borutta • T. Emrich • M. Berrendorf • M. Schubert
Graph Alignment Networks with Node Matching Scores.
Graph Representation Learning @NeurIPS 2019 - Workshop on Graph Representation Learning at the 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. PDF

[32]

M. Biloš • B. Charpentier • S. Günnemann
Uncertainty on Asynchronous Time Event Prediction.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

[31]

A. Bojchevski • S. Günnemann
Certifiable Robustness to Graph Perturbations.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

[30]

J. Gasteiger • S. Weißenberger • S. Günnemann
Diffusion Improves Graph Learning.
NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 08-14, 2019. URL

[29]

D. Mautz • C. Plant • C. Böhm
Deep Embedded Cluster Tree.
ICDM 2019 - 19th IEEE International Conference on Data Mining. Beijing, China, Nov 08-11, 2019. DOI

[28]

E. Faerman • M. Rogalla • N. Strauß • A. Krüger • B. Blümel • M. Berrendorf • M. Fromm • M. Schubert
Spatial Interpolation with Message Passing Framework.
Workshop @ICDM 2019 - Workshop at the 19th IEEE International Conference on Data Mining. Beijing, China, Nov 08-11, 2019. DOI

[27]

M. Fromm • M. Berrendorf • E. Faerman • Y. Chen • B. Schüss • M. Schubert
XD-STOD: Cross-Domain Superresolution for Tiny Object Detection.
Workshop @ICDM 2019 - Workshop at the 19th IEEE International Conference on Data Mining. Beijing, China, Nov 08-11, 2019. DOI

[26]

F. Lüer • D. Mautz • C. Böhm
Anomaly Detection in Time Series using Generative Adversarial Networks.
Workshop @ICDM 2019 - Workshop at the 19th IEEE International Conference on Data Mining. Beijing, China, Nov 08-11, 2019. DOI

[25]

F. Borutta • S. Schmoll • S. Friedl
Optimizing the Spatio-Temporal Resource Search Problem with Reinforcement Learning.
ACM SIGSPATIAL 2019 - 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Chicago, ILL, USA, Nov 05-08, 2019. DOI

[24]

F. Borutta • J. Busch • E. Faerman • A. Klink • M. Schubert
Structural Graph Representations based on Multiscale Local Network Topologies.
WI 2019 - IEEE/WIC/ACM International Conference on Web Intelligence. Thessaloniki, Greece, Oct 14-17, 2019. DOI

[23]

M. Fromm • E. Faerman • T. Seidl
TACAM: Topic And Context Aware Argument Mining.
WI 2019 - IEEE/WIC/ACM International Conference on Web Intelligence. Thessaloniki, Greece, Oct 14-17, 2019. DOI

[22]

A. Beer • J. Lauterbach • T. Seidl
MORe++: k-Means Based Outlier Removal on High-Dimensional Data.
SISAP 2019 - 12th International Conference on Similarity Search and Applications. Newark, New York, USA, Oct 02-04, 2019. DOI

[21]

M. Berrendorf • F. Borutta • P. Kröger
k-Distance Approximation for Memory-Efficient RkNN Retrieval.
SISAP 2019 - 12th International Conference on Similarity Search and Applications. Newark, New York, USA, Oct 02-04, 2019. DOI

[20]

F. Borutta • P. Kröger • T. Hubauer
A Generic Summary Structure for Arbitrarily Oriented Subspace Clustering in Data Streams.
SISAP 2019 - 12th International Conference on Similarity Search and Applications. Newark, New York, USA, Oct 02-04, 2019. DOI

[19]

M. A. X. Hünemörder • D. Kazempour • P. Kröger • T. Seidl
SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge.
SISAP 2019 - 12th International Conference on Similarity Search and Applications. Newark, New York, USA, Oct 02-04, 2019. DOI

[18]

D. Kazempour • M. Hünemörder • T. Seidl
On coMADs and Principal Component Analysis.
SISAP 2019 - 12th International Conference on Similarity Search and Applications. Newark, New York, USA, Oct 02-04, 2019. DOI

[17]

A. Beer • N. S. Schüler • T. Seidl
A Generator for Subspace Clusters.
LWDA 2019 - Conference on Lernen. Wissen. Daten. Analysen. Berlin, Germany, Sep 30-Oct 02, 2019. PDF

[16]

D. Kazempour • A. Beer • O. Schrüfer • T. Seidl
Clustering Trend Data Time-Series through Segmentation of FFT-decomposed Signal Constituents.
LWDA 2019 - Conference on Lernen. Wissen. Daten. Analysen. Berlin, Germany, Sep 30-Oct 02, 2019. PDF

[15]

D. Kazempour • L. M. Yan • T. Seidl
From Covariance to Comode in context of Principal Component Analysis.
LWDA 2019 - Conference on Lernen. Wissen. Daten. Analysen. Berlin, Germany, Sep 30-Oct 02, 2019. PDF

[14]

J. Held • A. Beer • T. Seidl
Chain-detection Between Clusters.
Datenbank-Spektrum 19. Sep. 2019. DOI

[13]

S. Schmoll • S. Friedl • M. Schubert
Scaling the Dynamic Resource Routing Problem.
SSTD 2019 - 16th International Symposium on Spatial and Temporal Databases. Vienna, Austria, Aug 19-21, 2019. DOI

[12]

A. Beer • D. Kazempour • M. Baur • T. Seidl
Human Learning in Data Science (Poster Extended Abstract).
HCII 2019 - 21st International Conference of Human-Computer Interaction. Orlando, Florida, USA, Jul 26-31, 2019. DOI

[11]

D. Kazempour • A. Beer • T. Seidl
Data on RAILs: On interactive generation of artificial linear correlated data (Poster Extended Abstract).
HCII 2019 - 21st International Conference of Human-Computer Interaction. Orlando, Florida, USA, Jul 26-31, 2019. DOI

[10]

A. Beer • D. Kazempour • L. Stephan • T. Seidl
LUCK - Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function (short paper).
SSDBM 2019 - 31st International Conference on Scientific and Statistical Database Management. Santa Cruz, CA, USA, Jul 23-25, 2019. DOI

[9]

A. Beer • T. Seidl
Graph Ordering and Clustering - A Circular Approach.
SSDBM 2019 - 31st International Conference on Scientific and Statistical Database Management. Santa Cruz, CA, USA, Jul 23-25, 2019. DOI

[8]

D. Kazempour • K. Emmerig • P. Kröger • T. Seidl
Detecting Global Periodic Correlated Clusters in Event Series based on Parameter Space Transform.
SSDBM 2019 - 31st International Conference on Scientific and Statistical Database Management. Santa Cruz, CA, USA, Jul 23-25, 2019. DOI

[7]

D. Kazempour • T. Seidl
On systematic hyperparameter analysis through the example of subspace clustering.
SSDBM 2019 - 31st International Conference on Scientific and Statistical Database Management. Santa Cruz, CA, USA, Jul 23-25, 2019. DOI

[6]

A. Bojchevski • S. Günnemann
Adversarial Attacks on Node Embeddings via Graph Poisoning.
ICML 2019 - 36th International Conference on Machine Learning. Long Beach, CA, USA, Jun 09-15, 2019. URL

[5]

A. Beer • D. Kazempour • T. Seidl
Rock - Let the points roam to their clusters themselves.
EDBT 2019 - 22nd International Conference on Extending Database Technology. Lisbon, Portugal, Mar 26-29, 2019. PDF

[4]

D. Kazempour • L. Krombholz • P. Kröger • T. Seidl
A Galaxy of Correlations - Detecting Linear Correlated Clusters through k-Tuples Sampling using Parameter Space Transform.
EDBT 2019 - 22nd International Conference on Extending Database Technology. Lisbon, Portugal, Mar 26-29, 2019. PDF

[3]

D. Kazempour • T. Seidl
Insights into a running clockwork: On interactive process-aware clustering.
EDBT 2019 - 22nd International Conference on Extending Database Technology. Lisbon, Portugal, Mar 26-29, 2019. PDF

[2]

D. Kazempour • M. Kazakov • P. Kröger • T. Seidl
DICE: Density-based Interactive Clustering and Exploration.
BTW 2019 - 18th Symposium of Database Systems for Business, Technology and Web. Rostock, Germany, Mar 04-08, 2019. DOI

[1]

D. Mautz • W. Ye • C. Plant • C. Böhm
Discovering Non-Redundant K-means Clusterings in Optimal Subspaces.
KDD 2018 - 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. London, UK, Aug 19-23, 2018. DOI

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2022-12-29 - Last modified: 2026-02-04