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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.

Principal Investigator

Algorithmic Machine Learning & Explainable AI

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

Anne-Laure Boulesteix

Prof. Dr.

Principal Investigator

Biometry in Molecular Medicine

Andreas Döpp

Dr. habil

Associate

Data-driven methods in Physics and Optics

Mathias Drton

Prof. Dr.

Principal Investigator

Mathematical Statistics

Stefan Feuerriegel

Prof. Dr.

Principal Investigator

Artificial Intelligence in Management

Vincent Fortuin

Dr.

Associate

Bayesian Deep Learning

Fabian Fumagalli

Prof. Dr.

Thomas Bayes Fellow

Statistical Learning and Data Science

Debarghya Ghoshdastidar

Prof. Dr.

Principal Investigator

Theoretical Foundations of Artificial Intelligence

Gjergji Kasneci

Prof. Dr.

Principal Investigator

Responsible Data Science

Göran Kauermann

Prof. Dr.

Principal Investigator

Applied Statistics in Social Sciences, Economics and Business

Thomas Nagler

Prof. Dr.

Principal Investigator

Computational Statistics & Data Science

David Rügamer

Prof. Dr.

Principal Investigator

Statistics, Data Science and Machine Learning

Fabian Scheipl

PD Dr.

Principal Investigator

Functional Data Analysis

Volker Schmid

Prof. Dr.

Principal Investigator

Bayesian Imaging & Spatial Statistics

Michael Schomaker

Prof. Dr.

Associate

Biostatistics

©all images: LMU | TUM

Publications in Research Area A1

[590]

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. To be published. Preprint available. URL

[589]

Y. Wang • D. Frauen • J. Schweisthal • 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. To be published. Preprint available. URL

[588]

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. To be published. Preprint available. URL

[587]

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. To be published. Preprint available. URL

[586]

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. To be published. Preprint available. URL

[585]

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. To be published. Preprint available. URL

[584]

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. To be published. Preprint available. arXiv

[583]

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. To be published. Preprint available. arXiv

[582]

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. To be published. Preprint available. arXiv

[581]

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. To be published. Preprint available. arXiv GitHub

[580]

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. To be published. Preprint available. arXiv

[579]

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

[578]

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. To be published. Preprint available. URL

[577]

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. To be published. Preprint available. DOI

[576]

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. Oct. 2025. DOI

[575]

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

[574]

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

[573]

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

[572]

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

[571]

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

[570]

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

[569]

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. Oct. 2025. To be published.

[568]

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.
Preprint (Oct. 2025). arXiv

[567]

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

[566]

E. Javurek • V. Melnychuk • J. Schweisthal • K. Hess • D. Frauen • S. Feuerriegel
An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes.
Preprint (Oct. 2025). arXiv

[565]

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

[564]

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

[563]

A. Maarouf • K. T. Greene • J. N. Shapiro • S. Feuerriegel • M. H. Ribeiro
Short-form video platforms drive mobile overuse.
Preprint (Oct. 2025). DOI

[562]

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

[561]

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

[560]

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

[559]

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

[558]

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

[557]

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. To be published. Preprint available. arXiv

[556]

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

[555]

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

[554]

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

[553]

T. Zehle • M. Schlager • T. Heiß • M. Feurer
CAPO: Cost-Aware Prompt Optimization.
AutoML 2025 - International Conference on Automated Machine Learning. New York City, NY, USA, Sep 08-11, 2025. To be published. Preprint available. arXiv

[552]

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

[551]

M. Brockschmidt • M. Schröder • S. Feuerriegel
SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis.
Preprint (Sep. 2025). arXiv

[550]

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

[549]

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

[548]

V. Melnychuk • S. Feuerriegel
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes.
Preprint (Sep. 2025). arXiv

[547]

V. Melnychuk • D. Frauen • J. Schweisthal • S. Feuerriegel
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation.
Preprint (Sep. 2025). arXiv

[546]

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

[545]

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

[544]

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

[543]

J. Zobolas • A.-M. George • A. López • S. 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

[542]

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

[541]

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

[540]

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

[539]

R. Schwank • M. Drton
On the distance between mean and geometric median in high dimensions.
Preprint (Aug. 2025). arXiv

[538]

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.
Preprint (Aug. 2025). DOI

[537]

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

[536]

S. Urchs • V. Thurner • M. Aßenmacher • C. Heumann • S. Thiemichen
Fair Play in the Newsroom: Actor-Based Filtering Gender Discrimination in Text Corpora.
Preprint (Aug. 2025). arXiv

[535]

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

[534]

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

[533]

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. URL

[532]

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. URL

[531]

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

[530]

S. 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

[529]

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. URL

[528]

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

[527]

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

[526]

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

[525]

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

[524]

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

[523]

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

[522]

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

[521]

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

[520]

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

[519]

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. To be published. Preprint available. arXiv

[518]

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

[517]

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

[516]

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

[515]

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

[514]

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

[513]

B. Bischl • G. Casalicchio • T. Das • M. Feurer • S. 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

[512]

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

[511]

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

[510]

D. Geissler • C. Robertson • S. Feuerriegel
Digital literacy interventions can boost humans in discerning deepfakes.
Preprint (Jul. 2025). arXiv

[509]

C. Gruber • H. Alber • B. Bischl • G. Kauermann • B. Plank • M. Aßenmacher
Revisiting Active Learning under (Human) Label Variation.
Preprint (Jul. 2025). arXiv

[508]

Y. Ozyurt • T. Almaci • S. Feuerriegel • M. Sachan
Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing.
Preprint (Jul. 2025). arXiv

[507]

B. Pulido • A. M. Franco-Pereira • R. E. Lillo • F. Scheipl
Area-based epigraph and hypograph indices for functional outlier detection.
Preprint (Jul. 2025). arXiv

[506]

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

[505]

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

[504]

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

[503]

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

[502]

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 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. DOI

[501]

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

[500]

C. Wu • B. Ma • Z. Zhang • N. Deng • Y. He • Y. Xue
Evaluating Zero-Shot Multilingual Aspect-Based Sentiment Analysis with Large Language Models.
International Journal of Machine Learning and Cybernetics. Jun. 2025. DOI

[499]

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

[498]

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

[497]

C. Benjamins • H. Graf • S. Segel • D. Deng • T. Ruhkopf • L. Hennig • S. Basu • N. Mallik • E. Bergman • D. Chen • F. Clément • M. Feurer • K. Eggensperger • F. Hutter • C. Doerr • M. Lindauer
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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

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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

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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

[386]

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

[385]

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

[384]

T. Pielok • B. Bischl • D. Rügamer
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent.
Preprint (Oct. 2024). arXiv

[383]

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

[382]

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

[381]

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

[380]

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

[379]

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

[378]

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

[377]

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

[376]

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

[375]

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

[374]

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

[373]

A. Bashardoust • Y. Feng • D. Geißler • S. Feuerriegel • Y. R. Shrestha
The Effect of Education in Prompt Engineering: Evidence from Journalists.
Preprint (Sep. 2024). arXiv

[372]

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

[371]

A. Stephan • D. Zhu • M. Aßenmacher • X. Shen • B. Roth
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks.
Preprint (Sep. 2024). arXiv

[370]

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

[369]

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. URL

[368]

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

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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

[366]

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

[365]

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

[364]

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

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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

[362]

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

[361]

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

[360]

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

[359]

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

[358]

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

[357]

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

[356]

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

[355]

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

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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

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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

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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

[351]

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

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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

[349]

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

[348]

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

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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

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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

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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

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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

[343]

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

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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

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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

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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

[339]

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

[338]

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

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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

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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

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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 08-22, 2024. arXiv GitHub

[334]

S. Fischer • M. Binder
mlr3torch - Deep Learning in R.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-22, 2024. GitHub

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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

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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

[331]

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

[330]

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

[329]

M. Schröder • D. Frauen • J. Schweisthal • K. Heß • V. Melnychuk • S. Feuerriegel
Conformal Prediction for Causal Effects of Continuous Treatments.
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[328]

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

[327]

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

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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

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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. URL

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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

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

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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

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D. Bär • F. Pierri • G. De Francisci Morales • S. Feuerriegel
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PNAS Nexus.pgae247. Jun. 2024. DOI

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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

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B. Felderer • L. Repke • W. Weber • J. Schweisthal • L. Bothmann
Predicting the Validity and Reliability of Survey Questions.
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E. Dorigatti
Cancer immunotherapy design and analysis through discrete optimization, positive-unlabeled learning, and semi-structured regression models.
Dissertation LMU München. May. 2024. DOI

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C. A. Scholbeck
Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations.
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K. Röck
Stochastic processes as surrogate models for dynamical systems in magnetic confinement fusion.
Dissertation LMU München. May. 2024. DOI

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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K. Heß • D. Frauen • V. Melnychuk • S. Feuerriegel
G-Transformer for Conditional Average Potential Outcome Estimation over Time.
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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

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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

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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

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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

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

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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

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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

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V. Gkolemis • C. Diou • E. Ntoutsi • T. Dalamagas • B. Bischl • J. Herbinger • G. Casalicchio
Effector: A Python package for regional explanations.
Preprint (Apr. 2024). arXiv GitHub

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M. Wünsch • M. Herrmann • E. Noltenius • M. Mohr • T. P. Morris • A.-L. Boulesteix
On the handling of method failure in comparison studies.
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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

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What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Annals of Applied Statistics 18.1. Mar. 2024. DOI

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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

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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

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M. Maritsch • S. Föll • V. Lehmann • N. Styger • C. Bérubé • M. Kraus • S. Feuerriegel • T. Kowatsch • T. Züger • E. Fleisch • F. Wortmann • C. Stettler
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Diabetes, Obesity and Metabolism 26.3. Mar. 2024. DOI

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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

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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

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

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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

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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

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

[281]

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

[280]

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

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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

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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

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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

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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

[275]

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

[274]

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

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

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

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

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

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

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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

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

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

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

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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

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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

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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

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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

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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.
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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

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

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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

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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

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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. URL

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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. URL

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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. URL

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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. URL

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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

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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) - BabyLM Challenge at the 27th Conference on Computational Natural Language Learning. Singapore, Dec 06-10, 2023. DOI GitHub

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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

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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

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

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Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview.
ACM Transactions on Evolutionary Learning and Optimization 3.4. Dec. 2023. DOI

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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

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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

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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

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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

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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

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Second-Order Uncertainty Quantification: Variance-Based Measures.
Preprint (Dec. 2023). arXiv

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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

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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

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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

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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

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

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

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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

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

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J. Gauss • F. Scheipl • M. Herrmann
DCSI–An improved measure of cluster separability based on separation and connectedness.
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Y. Ma • D. Frauen • V. Melnychuk • S. Feuerriegel
Counterfactual Fairness for Predictions using Generative Adversarial Networks.
Preprint (Oct. 2023). arXiv

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I. Ziegler • B. Ma • B. Bischl • E. Dorigatti • B. Schubert
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Preprint (Oct. 2023). DOI GitHub

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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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

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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

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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

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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

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

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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

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

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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

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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

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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

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

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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

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

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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

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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

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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

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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

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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

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

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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

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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

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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

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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

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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

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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

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B. X. W. Liew • D. Rügamer • Q. Mei • Z. Altai • X. Zhu • X. Zhai • N. Cortes
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Frontiers in Bioengineering and Biotechnology 11. Jul. 2023. DOI

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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

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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

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M. Aßenmacher • N. Sauter • C. Heumann
Classifying multilingual party manifestos: Domain transfer across country, time, and genre.
Preprint (Jul. 2023). arXiv

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

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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

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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

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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

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J. Moosbauer
Towards explainable automated machine learning.
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PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI

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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

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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

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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

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N. Banholzer • T. Mellan • H. J. T. Unwin • S. Feuerriegel • S. Mishra • S. Bhatt
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Preprint (May. 2023). arXiv

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

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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

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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

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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

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N. Pröllochs • S. Feuerriegel
Mechanisms of True and False Rumor Sharing in Social Media: Collective Intelligence or Herd Behavior?
CHI 2023 - Conference on Human Factors in Computing Systems. Hamburg, Germany, Apr 23-28, 2023. DOI

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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

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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

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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

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S. Dandl • A. Hofheinz • M. Binder • B. Bischl • G. Casalicchio
counterfactuals: An R Package for Counterfactual Explanation Methods.
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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

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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

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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

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

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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

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Estimating Average Causal Effects from Patient Trajectories.
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI

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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

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

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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

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

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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

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D. Rügamer
mixdistreg: An R Package for Fitting Mixture of Experts Distributional Regression with Adaptive First-order Methods.
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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

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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. URL

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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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

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

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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

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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

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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

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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

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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

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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

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

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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

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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

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E. Dorigatti • B. Bischl • B. Schubert
Improved proteasomal cleavage prediction with positive-unlabeled learning.
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E. Dorigatti • J. Schweisthal • B. Bischl • M. Rezaei
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision.
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C. A. Scholbeck • H. Funk • G. Casalicchio
Algorithm-Agnostic Interpretations for Clustering.
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S.-F. Zheng • J. Nam • E. Dorigatti • B. Bischl • S. Azizi • M. Rezaei
Joint Debiased Representation and Image Clustering Learning with Self-Supervision.
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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

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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

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

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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

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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.
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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.
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C. Fritz
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Dissertation LMU München. Jul. 2022. DOI

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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

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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

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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

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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

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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

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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

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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

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

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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

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

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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

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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

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D. Rügamer
Additive Higher-Order Factorization Machines.
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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

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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

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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

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Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
Scientific Reports 12.3930. Mar. 2022. DOI

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C. Sauer • M. Herrmann • C. Wiedemann • G. Casalicchio • A.-L. Boulesteix
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Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12.2. Mar. 2022. DOI

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Cross-Modal Common Representation Learning with Triplet Loss Functions.
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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

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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

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

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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

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tf: S3 classes and methods for tidy functional data. R package.
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J. Goldsmith • F. Scheipl
tidyfun: Clean, wholesome, tidy fun with functional data in R. R package.
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W. Hartl • P. Kopper • A. Bender • F. Scheipl • A. G. Day • G. Elke • H. Küchenhoff
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C. Fritz • G. Kauermann
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Journal of the Royal Statistical Society. Series A (Statistics in Society) 185.1. Jan. 2022. DOI

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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

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E. Dorigatti • J. Goschenhofer • B. Schubert • M. Rezaei • B. Bischl
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection.
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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

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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

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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

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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

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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

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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

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

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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

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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

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

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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

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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

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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

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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

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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

[79]

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

[78]

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

[77]

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

[76]

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

[75]

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

[74]

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

[73]

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

[72]

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

[71]

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

[70]

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

[69]

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

[68]

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

[67]

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

[66]

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

[65]

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

[64]

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

[63]

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

[62]

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

[61]

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

[60]

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

[59]

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

[58]

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

[57]

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

[56]

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

[55]

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

[54]

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

[53]

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

[52]

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

[51]

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

[50]

P. F. M. Baumann • T. Hothorn • D. Rügamer
Deep Conditional Transformation Models.
Preprint (Oct. 2020). arXiv

[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.

Principal Investigator

Applied Topology and Geometry

Felix Dietrich

Prof. Dr.

Associate

Physics-enhanced Machine Learning

Massimo Fornasier

Prof. Dr.

Principal Investigator

Applied Numerical Analysis

Reinhard Heckel

Prof. Dr.

Principal Investigator

Machine Learning and Information Processing

Felix Krahmer

Prof. Dr.

Principal Investigator

Optimization & Data Analysis

Christian Kühn

Prof. Dr.

Associate

Multiscale and Stochastic Dynamics

Gitta Kutyniok

Prof. Dr.

Principal Investigator

Mathematical Foundations of Artificial Intelligence

Johannes Maly

Prof. Dr.

Associate

Mathematical Data Science and Artificial Intelligence

Holger Rauhut

Prof. Dr.

Principal Investigator

Mathematical Data Science and Artificial Intelligence

Suvrit Sra

Prof. Dr.

Principal Investigator

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

[151]

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. To be published. Preprint available. URL

[150]

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. To be published. Preprint available. URL

[149]

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. To be published. Preprint available. 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. 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. To be published. Preprint available. URL

[146]

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

[145]

J. E. S. Cardona • H. Boche • G. Kutyniok
A Variational Framework for the Algorithmic Complexity of PDE Solutions.
Preprint (Oct. 2025). arXiv

[144]

C. Kneissl • C. Bülte • P. Scholl • G. Kutyniok
Improved probabilistic regression using diffusion models.
Preprint (Oct. 2025). arXiv

[143]

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

[142]

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

[141]

N. Derevianko • I. G. Kevrekidis • F. Dietrich
Neural network-based singularity detection and applications.
Preprint (Sep. 2025). arXiv

[140]

A. Scagliotti • S. Farinelli
Normalizing flows as approximations of optimal transport maps via linear-control neural ODEs.
Nonlinear Analysis 257.113811. Aug. 2025. DOI

[139]

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

[138]

F. Krahmer • F. Pagginelli Patricio • P. Catala
On a Recovery Method with Approximation Guarantees for Noisy Unlimited Sampling.
SampTA 2025 - 15th International Conference on Sampling Theory and Applications. Vienna, Austria, Jul 28-Aug 01, 2025. To be published. Preprint available. URL

[137]

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. To be published. Preprint available. DOI

[136]

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

[135]

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. To be published. Preprint available. DOI

[134]

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

[133]

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

[132]

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

[131]

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

[130]

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

[129]

E. M. Achour • K. Kohn • H. Rauhut
The Riemannian Geometry associated to Gradient Flows of Linear Convolutional Networks.
Preprint (Jul. 2025). arXiv

[128]

D. Chemnitz • M. Engel • C. Kühn • S.-V. Kuntz
A Dynamical Systems Perspective on the Analysis of Neural Networks.
Preprint (Jul. 2025). arXiv

[127]

J. Li • G. Kutyniok
Expressivity of deep neural networks.
Preprint (Jul. 2025). PDF

[126]

F. Weindel • M. Girsch • R. Heckel
Trace Reconstruction with Language Models.
Preprint (Jul. 2025). arXiv

[125]

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

[124]

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

[123]

E. Pozzoli • A. Scagliotti
Approximation of diffeomorphisms for quantum state transfers.
IEEE Control Systems Letters Early Access. Jun. 2025. DOI

[122]

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

[121]

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

[120]

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

[119]

S. Almi • M. Fornasier • J. Klemenc • A. Scagliotti
Balanced quasistatic evolutions of critical points in metric spaces.
Preprint (Jun. 2025). arXiv

[118]

A. Bergmeister • M. K. Lal • S. Jegelka • S. Sra
A projection-based framework for gradient-free and parallel learning.
Preprint (Jun. 2025). arXiv

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AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL

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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

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ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL

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European Journal of Applied Mathematics 36.Special Issue 2: From integro-differential models to data-oriented approaches for emergent phenomena. Apr. 2025. DOI

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International Journal for Uncertainty Quantification 15.4. Mar. 2025. DOI

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Math4AiMl 2025 - 3rd Workshop of UMI Group Mathematics for Artificial Intelligence and Machine Learning. Bari, Italy, Jan 29-31, 2025. arXiv PDF

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CDC 2024 - 63rd IEEE Conference on Decision and Control. Milan, Italy, Dec 16-19, 2024. DOI

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NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

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NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL

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NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL GitHub

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MICCAI 2024 - 27th International Conference on Medical Image Computing and Computer Assisted Intervention. Marrakesh, Morocco, Oct 06-10, 2024. DOI

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ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI GitHub

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Mathematical Foundations of Interacting Multi-Particle Systems for Optimization.
Dissertation TU München. Sep. 2024. URL

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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

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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

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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

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FedCSIS 2024 - 19th Conference on Computer Science and Intelligence Systems. Belgrade, Serbia, Sep 08-11, 2024. DOI

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ISIT 2024 - IEEE International Symposium on Information Theory. Athens, Greece, Jul 07-12, 2024. DOI

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COLT 2024 - 37th Annual Conference on Learning Theory. Edmonton, Canada, Jun 30-Jul 03, 2024. URL

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IEEE Open Journal of Signal Processing 5. Jun. 2024. DOI

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NLDL 2024 - Northern Lights Deep Learning Conference. Tromsø, Norway, Jan 09-11, 2024. URL

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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

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Applied and Computational Harmonic Analysis 67. Nov. 2023. 2024 ACHA Charles Chui Young Researcher Best Paper Award. DOI

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MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI

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MLSP 2023 - IEEE Workshop on Machine Learning for Signal Processing. Rome, Italy, Sep 17-20, 2023. DOI

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Partial Differential Equations and Applications 4.40. Aug. 2023. DOI

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ICML 2023 - 40th International Conference on Machine Learning. Honolulu, Hawaii, Jul 23-29, 2023. URL GitHub

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SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

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SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

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SampTA 2023 - 14th International Conference on Sampling Theory and Applications. Yale, CT, USA, Jul 10-14, 2023. DOI

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European Congress of Mathematics. Jul. 2023. DOI

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SIAM Journal on Imaging Sciences 16.3. Jul. 2023. DOI

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CVPR 2023 - IEEE/CVF Conference on Computer Vision and Pattern Recognition. Vancouver, Canada, Jun 18-23, 2023. DOI

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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

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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

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Applied Mathematics and Optimization 88.2. May. 2023. DOI

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ICLR 2023 - 11th International Conference on Learning Representations. Kigali, Rwanda, May 01-05, 2023. URL

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ESAIM - Control, Optimisation and Calculus of Variations 29.22. Mar. 2023. DOI

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Dissertation TU München. Dec. 2022. URL

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NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

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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. URL

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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. URL

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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]

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

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.

Associate

Technology and Research on Artificial Intelligence

Stephan Günnemann

Prof. Dr.

Principal Investigator

Data Analytics & Machine Learning

Eyke Hüllermeier

Prof. Dr.

Principal Investigator

Artificial Intelligence and Machine Learning

Stefanie Jegelka

Prof. Dr.

Principal Investigator

Foundations of Deep Neural Networks

Niki Kilbertus

Prof. Dr.

Principal Investigator

Ethics in Systems Design and Machine Learning

Johannes Kinder

Prof. Dr.

Associate

Programming Languages and Artificial Intelligence

Marcus Paradies

Prof. Dr.

Associate

Database Systems, Data Mining and AI

Steffen Schneider

Dr.

Associate

Dynamical Inference

Matthias Schubert

Prof. Dr.

Principal Investigator

Spatial Artificial Intelligence

Thomas Seidl

Prof. Dr.

Director

Database Systems, Data Mining and AI

Volker Tresp

Prof. Dr.

Principal Investigator

Database Systems, Data Mining and AI

©all images: LMU | TUM

Publications in Research Area A3

[479]

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. To be published. Preprint available. URL

[478]

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. To be published. Preprint available. URL

[477]

T. Kaufmann • Y. Metz • D. Keim • E. Hüllermeier
RtRank: Stratified Response Time Ranking for Data-Efficient Reward Modeling.
NeurIPS 2025 - 39th Conference on Neural Information Processing Systems. San Diego, CA, USA, Nov 30-Dec 07, 2025. To be published. URL

[476]

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. To be published. Preprint available. URL

[475]

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. To be published. Preprint available. URL

[474]

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. To be published. Preprint available. URL

[473]

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. To be published. Preprint available. URL

[472]

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. To be published. Preprint available. URL

[471]

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. To be published. Preprint available. URL

[470]

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. To be published. Preprint available. URL

[469]

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. To be published. Preprint available. arXiv GitHub

[468]

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. To be published. Preprint available. URL

[467]

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. To be published. Preprint available. URL

[466]

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. To be published.

[465]

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. To be published. Preprint available. arXiv GitHub

[464]

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. To be published. Preprint available.

[463]

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. To be published. Preprint available. arXiv

[462]

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. To be published. Preprint available. arXiv GitHub

[461]

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. To be published. Preprint available. arXiv GitHub

[460]

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. To be published. Preprint available. arXiv

[459]

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. To be published.

[458]

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

[457]

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. To be published. Preprint available. URL

[456]

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. To be published. Preprint available. arXiv

[455]

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

[454]

P. Foth • L. Gosch • S. Geisler • L. Schwinn • S. Günnemann
Adversarial Robustness of Graph Transformers.
Transactions on Machine Learning Research. Oct. 2025. URL

[453]

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

[452]

Z. Cao • X. Zhao • L. Krieger • H. Scharr • I. Assent
LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching.
Preprint (Oct. 2025). arXiv

[451]

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.
Preprint (Oct. 2025). arXiv GitHub

[450]

A. Findeis • T. Kaufmann • E. Hüllermeier • R. Mullins
Feedback Forensics: A Toolkit to Measure AI Personality.
Preprint (Oct. 2025). arXiv GitHub

[449]

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.
Preprint (Oct. 2025). arXiv

[448]

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

[447]

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.
Preprint (Oct. 2025). arXiv

[446]

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

[445]

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

[444]

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

[443]

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

[442]

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

[441]

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. To be published.

[440]

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

[439]

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. Sep. 2025. DOI

[438]

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

[437]

F. Liu • R. Zhao • S. Chen • G. Li • P. Torr • L. Han • J. Gu
Can an Individual Manipulate the Collective Decisions of Multi-Agents?
Preprint (Sep. 2025). arXiv

[436]

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.
Preprint (Sep. 2025). arXiv

[435]

J. Schooling • T. Meier • M. Amutorine
Social Impact of LLMs: The Ups, the Downs and the Uncharted Waters.
Preprint (Sep. 2025). DOI

[434]

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.
Preprint (Sep. 2025). arXiv

[433]

A. Wang • X. Wu • D. Shu • Y. Ma • N. Liu
Enhancing LLM Steering through Sparse Autoencoder-Based Vector Refinement.
Preprint (Sep. 2025). arXiv

[432]

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

[431]

Y. Sun • M. Hagog • M. Weber • D. Hein • S. Udluft • V. Tresp • Y. Ma
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. To be published. Preprint available. arXiv

[430]

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

[429]

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

[428]

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

[427]

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

[426]

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

[425]

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. URL

[424]

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. URL GitHub

[423]

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. URL

[422]

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. URL GitHub

[421]

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

[420]

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

[419]

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

[418]

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

[417]

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

[416]

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

[415]

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

[414]

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

[413]

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

[412]

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

[411]

L. Rottkamp
Obtaining, improving and evaluating spatio-temporal information for efficient solutions of mobility problems.
Dissertation LMU München. Jul. 2025. DOI

[410]

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

[409]

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

[408]

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

[407]

Y. Sale • A. Ramdas
Online Selective Conformal Prediction: Errors and Solutions.
Transactions on Machine Learning Research. Jul. 2025. URL

[406]

S. Haas • E. Hüllermeier
Aleatoric and Epistemic Uncertainty Measures for Ordinal Classification through Binary Reduction.
Preprint (Jul. 2025). arXiv

[405]

T. Meier • K. Khutsishvili
Who Owns the Future? Ways to Understand Power, Technology, and the Moral Commons.
Preprint (Jul. 2025). URL

[404]

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 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN, USA, Jun 11-15, 2025. Best Paper Award. URL GitHub

[403]

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

[402]

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

[401]

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

[400]

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

[399]

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

[398]

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

[397]

V. Margraf • T. Koerner • A. Tornede • M. Wever
RunAndSchedule2Survive: Algorithm Scheduling Based on Run2Survive.
ACM Transactions on Evolutionary Learning and Optimization Just accepted. Jun. 2025. DOI

[396]

P. Gupta • M. Wever • E. Hüllermeier
Information Leakage Detection through Approximate Bayes-optimal Prediction.
Information Sciences In Press, Journal Pre-proof.122419. Jun. 2025. DOI

[395]

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

[394]

T. Kaufmann • P. Weng • V. Bengs • E. Hüllermeier
A Survey of Reinforcement Learning from Human Feedback.
Transactions on Machine Learning Research. Jun. 2025. URL

[393]

A. Bergmeister • M. K. Lal • S. Jegelka • S. Sra
A projection-based framework for gradient-free and parallel learning.
Preprint (Jun. 2025). arXiv

[392]

C. Casolo • S. Becker • N. Kilbertus
Identifiability Challenges in Sparse Linear Ordinary Differential Equations.
Preprint (Jun. 2025). arXiv

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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

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DS 2024 - 27th International Conference on Discovery Science. Pisa, Italy, Oct 14-16, 2024. DOI GitHub

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Doctoral Consortium @ICPM 2024 - Doctoral Consortium at the 6th International Conference on Process Mining. Lyngby, Denmark, Oct 14-18, 2024. URL

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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

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ECCV 2024 - 18th European Conference on Computer Vision. Milano, Italy, Sep 29-Oct 04, 2024. DOI

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AutoML 2024 - ABCD Track - Track on Applications, Benchmarks, Challenges, and Datasets at the International Conference on Automated Machine Learning. Paris, France, Sep 09-12, 2024. URL

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ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

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ECML-PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Vilnius, Lithuania, Sep 09-13, 2024. DOI

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SDM 2023 - SIAM International Conference on Data Mining. Minneapolis, MN, USA, Apr 27-29, 2023. DOI

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AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI GitHub

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Computational Intelligence 2022 - 32nd Workshop on Computational Intelligence of the VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik. Berlin, Germany, Dec 01-02, 2022. PDF

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ICDM 2022 - 22nd IEEE International Conference on Data Mining. Orlando, FL, USA, Nov 30-Dec 02, 2022. DOI GitHub

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NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

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NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

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NeurIPS 2022 - 36th Conference on Neural Information Processing Systems. New Orleans, LA, USA, Nov 28-Dec 09, 2022. URL

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IJCRS 2022 - International Joint Conference on Rough Sets. Suzhou, China, Nov 11-14, 2022. DOI

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ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

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ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Grenoble, France, Sep 19-23, 2022. DOI

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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

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VLDB 2022 - 48th International Conference on Very Large Databases. Sydney, Australia (and hybrid), Sep 05-09, 2022. DOI GitHub

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KDD 2022 - 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Washington, DC, USA, Aug 14-18, 2022. DOI

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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

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BI 2022 - 15th International Conference on Brain Informatics. Padova, Italy, Jul 15-15, 2022. DOI GitHub

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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

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ICLR 2022 - 10th International Conference on Learning Representations. Virtual, Apr 25-29, 2022. URL GitHub

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GLB @WWW 2022 - Workshop on Graph Learning Benchmarks at the International World Wide Web Conference. Virtual, Apr 22-29, 2022. arXiv

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AAAI 2022 - 36th Conference on Artificial Intelligence. Virtual, Feb 22-Mar 01, 2022. DOI

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ISWC 2021 - 20th International Semantic Web Conference. Virtual, Oct 24-28, 2021. Best Paper Award. DOI GitHub

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Compound Segmentation via Clustering on Mol2Vec-based Embeddings.
eScience 2021 - 17th IEEE eScience Conference. Virtual, Sep 20-23, 2021. DOI

[93]

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

[92]

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

[91]

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

[90]

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

[89]

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

[88]

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

[87]

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

[86]

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

[85]

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

[84]

E. Faerman
Representation learning on relational data.
Dissertation LMU München. Apr. 2021. DOI

[83]

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

[82]

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

[81]

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

[80]

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

[79]

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

[78]

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

[77]

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

[76]

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

[75]

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

[74]

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

[73]

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

[72]

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

[71]

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

[70]

C. Böhm • C. Plant
Massively Parallel Random Number Generation.
IEEE BigData 2020 - IEEE International Conference on Big Data. Virtual, Dec 10-13, 2020. DOI

[69]

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

[68]

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

[67]

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

[66]

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

[65]

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

[64]

M. Berrendorf • E. Faerman
mberr/ea-active-learning: Zenodo. Version 1.0.1.
2020. DOI

[63]

M. Berrendorf • L. Wacker • E. Faerman
mberr/ea-sota-comparison: Zenodo. Version v1.1.1.
2020. DOI

[62]

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

[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]

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

[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

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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

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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

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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

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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

[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]

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

[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: 2025-10-29