Research Group Bernd Bischl
Bernd Bischl
Prof. Dr.
Director
Bernd Bischl
holds the Chair of Statistical Learning and Data Science at the Department of Statistics at LMU Munich.
He studied Computer Science, Artificial Intelligence and Data Sciences in Hamburg, Edinburgh and Dortmund and obtained his PhD from Dortmund Technical University in 2013 with a thesis on “Model and Algorithm Selection in Statistical Learning and Optimization”. His research interests include AutoML, Model Selection, Interpretable ML, as well as the development of Statistical Software. He is a member of ELLIS in general, and a faculty member of ELLIS Munich, an active developer of several R-packages, leads the “mlr” (Machine Learning in R) engineering group and is co-founder of the science platform “OpenML” for open and reproducible ML. Furthermore, he leads the Munich branch of the Fraunhofer ADA Lovelace Center for Analytics, Data & Applications, i.e. a new type of research infrastructure to support businesses in Bavaria, especially in the SME sector.
Team members @MCML
PostDocs
Matthias Aßenmacher
Dr.
→ Group Bernd Bischl
Statistical Learning and Data Science
Andreas Bender
Dr.
→ Group Bernd Bischl
Statistical Learning and Data Science
Ludwig Bothmann
Dr.
→ Group Bernd Bischl
Statistical Learning and Data Science
Giuseppe Casalicchio
Dr.
→ Group Bernd Bischl
Statistical Learning and Data Science
Mina Rezaei
Dr.
→ Group Bernd Bischl
Statistical Learning and Data Science
PhD Students
Helen Alber
→ Group Bernd Bischl
Statistical Learning and Data Science
Salem Ayadi
→ Group Bernd Bischl
Statistical Learning and Data Science
Marc Becker
→ Group Bernd Bischl
Statistical Learning and Data Science
Martin Binder
→ Group Bernd Bischl
Statistical Learning and Data Science
Coco Bögel
→ Group Bernd Bischl
Statistical Learning and Data Science
Philip Amir Boustani
→ Group Bernd Bischl
Statistical Learning and Data Science
Lukas Burk
→ Group Bernd Bischl
Statistical Learning and Data Science
Fiona Katharina Ewald
→ Group Bernd Bischl
Statistical Learning and Data Science
Sebastian Fischer
→ Group Bernd Bischl
Statistical Learning and Data Science
Esteban Garces Arias
→ Group Bernd Bischl
Statistical Learning and Data Science
Timo Heiß
→ Group Bernd Bischl
Statistical Learning and Data Science
Florian Karl
→ Group Bernd Bischl
Statistical Learning and Data Science
Chris Kolb
→ Group Bernd Bischl
Statistical Learning and Data Science
Yawei Li
→ Group Bernd Bischl
Statistical Learning and Data Science
Tobias Pielok
→ Group Bernd Bischl
Statistical Learning and Data Science
Simon Rittel
→ Group Bernd Bischl
Statistical Learning and Data Science
David Rundel
→ Group Bernd Bischl
Statistical Learning and Data Science
Lennart Schneider
→ Group Bernd Bischl
Statistical Learning and Data Science
Xiao-Yin To
→ Group Bernd Bischl
Statistical Learning and Data Science
Lisa Wimmer
→ Group Bernd Bischl
Statistical Learning and Data Science
Zizheng Zhang
→ Group Bernd Bischl
Statistical Learning and Data Science
Recent News @MCML
Publications @MCML
2025
[308]
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.
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.
[307]
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.
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.
[306]
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.
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.
[305]
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. GitHub
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. GitHub
[304]
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.
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.
[303]
S. Rittel • S. Tschiatschek
Expressiveness of Parametrized Distributions over DAGs for Causal Discovery.
Transactions on Machine Learning Research. Oct. 2025. URL
Expressiveness of Parametrized Distributions over DAGs for Causal Discovery.
Transactions on Machine Learning Research. Oct. 2025. URL
[302]
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
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
[301]
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
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
[300]
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
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
[299]
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.
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.
[298]
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
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
[297]
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
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
[296]
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
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
[295]
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.
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.
[294]
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).
Multi-state Models For Modeling Disease Histories Based On Longitudinal Data.
Preprint (Sep. 2025).
[293]
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).
Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data.
Preprint (Sep. 2025).
[292]
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).
Are All Genders Equal in the Eyes of Algorithms? -- Analysing Search and Retrieval Algorithms for Algorithmic Gender Fairness.
Preprint (Aug. 2025).
[291]
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).
Fair Play in the Newsroom: Actor-Based Filtering Gender Discrimination in Text Corpora.
Preprint (Aug. 2025).
[290]
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
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
[289]
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
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
[288]
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
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
[287]
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
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
[286]
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
Revisiting Unbiased Implicit Variational Inference.
ICML 2025 - 42nd International Conference on Machine Learning. Vancouver, Canada, Jul 13-19, 2025. URL
[285]
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
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
[284]
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
OpenML: Insights from 10 years and more than a thousand papers.
Patterns 6.7. Jul. 2025. DOI
[283]
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
Predictive modeling for step II therapy response in periodontitis - model development and validation.
npj Digital Medicine 8.445. Jul. 2025. DOI
[282]
C. Gruber • H. Alber • B. Bischl • G. Kauermann • B. Plank • M. Aßenmacher
Revisiting Active Learning under (Human) Label Variation.
Preprint (Jul. 2025).
Revisiting Active Learning under (Human) Label Variation.
Preprint (Jul. 2025).
[281]
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.
Privilege Scores.
EWAF 2025 - 4th European Workshop on Algorithmic Fairness. Eindhoven, The Netherlands, Jun 30-Jul 02, 2025.
[280]
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
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
[279]
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
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
[278]
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
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
[277]
M. Schöffel • E. Garces Arias • M. Wiedner • P. Ruppert • M. Li • C. Heumann • M. Aßenmacher
Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages.
Preprint (Jun. 2025).
Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages.
Preprint (Jun. 2025).
[276]
L. Schneider
Advancing hyperparameter optimization: foundations, multiple objectives and algorithmic innovations informed through benchmarking.
Dissertation LMU München. May. 2025. DOI
Advancing hyperparameter optimization: foundations, multiple objectives and algorithmic innovations informed through benchmarking.
Dissertation LMU München. May. 2025. DOI
[275]
H. Löwe • C. A. Scholbeck • C. Heumann • B. Bischl • G. Casalicchio
fmeffects: An R Package for Forward Marginal Effects.
The R Journal 16.3. May. 2025. DOI
fmeffects: An R Package for Forward Marginal Effects.
The R Journal 16.3. May. 2025. DOI
[274]
R. Sonabend • J. Zobolas • R. Bin • P. Kopper • L. Burk • A. Bender
Examining marginal properness in the external validation of survival models with squared and logarithmic losses.
Preprint (May. 2025).
Examining marginal properness in the external validation of survival models with squared and logarithmic losses.
Preprint (May. 2025).
[273]
C. Zhang • S. Wu • Y. Chen • M. Aßenmacher • C. Heumann • Y. Men • G. Fan • J. Gama
OBD-Finder: Explainable Coarse-to-Fine Text-Centric Oracle Bone Duplicates Discovery.
Preprint (May. 2025). GitHub
OBD-Finder: Explainable Coarse-to-Fine Text-Centric Oracle Bone Duplicates Discovery.
Preprint (May. 2025). GitHub
[272]
M. Schöffel • M. Wiedner • E. Garces Arias • P. Ruppert • C. Heumann • M. Aßenmacher
Modern Models, Medieval Texts: A POS Tagging Study of Old Occitan.
NLP4DH 2025 - 5th International Conference on Natural Language Processing for Digital Humanities. Albuquerque, NM, USA, Apr 29-May 04, 2025. DOI
Modern Models, Medieval Texts: A POS Tagging Study of Old Occitan.
NLP4DH 2025 - 5th International Conference on Natural Language Processing for Digital Humanities. Albuquerque, NM, USA, Apr 29-May 04, 2025. DOI
[271]
D. Rundel • E. Sommer • B. Bischl • D. Rügamer • M. Feurer
Efficiently Warmstarting MCMC for BNNs.
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
Efficiently Warmstarting MCMC for BNNs.
FPI @ICLR 2025 - Workshop on Frontiers in Probabilistic Inference: Learning meets Sampling at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
[270]
C. Kolb • T. Weber • B. Bischl • D. Rügamer
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
[269]
Y. Li • D. Rügamer • B. Bischl • M. Rezaei
Calibrating LLMs with Information-Theoretic Evidential Deep Learning.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
Calibrating LLMs with Information-Theoretic Evidential Deep Learning.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
[268]
H. Baniecki • G. Casalicchio • B. Bischl • P. Biecek
Efficient and Accurate Explanation Estimation with Distribution Compression.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL GitHub
Efficient and Accurate Explanation Estimation with Distribution Compression.
ICLR 2025 - 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. Spotlight Presentation. URL GitHub
[267]
L. Wimmer • B. Bischl • L. Bothmann
Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning.
SCSL @ICLR 2025 - Workshop on Spurious Correlation and Shortcut Learning: Foundations and Solutions at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning.
SCSL @ICLR 2025 - Workshop on Spurious Correlation and Shortcut Learning: Foundations and Solutions at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
[266]
C. Kolb • B. Bischl • D. Rügamer
Differentiable Attention Sparsity via Structured D-Gating.
SLLM @ICLR 2025 - Workshop on Sparsity in LLMs at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
Differentiable Attention Sparsity via Structured D-Gating.
SLLM @ICLR 2025 - Workshop on Sparsity in LLMs at the 13th International Conference on Learning Representations. Singapore, Apr 24-28, 2025. URL
[265]
H. A. Gündüz
Designing and optimizing deep learning methods for genomic sequencing data.
Dissertation LMU München. Apr. 2025. DOI
Designing and optimizing deep learning methods for genomic sequencing data.
Dissertation LMU München. Apr. 2025. DOI
[264]
T. Weber
Advancing Deep Learning in medical imaging through generative modeling and representation learning.
Dissertation LMU München. Apr. 2025. DOI
Advancing Deep Learning in medical imaging through generative modeling and representation learning.
Dissertation LMU München. Apr. 2025. DOI
[263]
M. Mironov • A. Marquard • D. Racek • C. Heumann • P. W. Thurner • M. Aßenmacher
A Geoparsing Pipeline for Multilingual Social Media Posts from Ukraine.
GeoExT @ECIR 2025 - 3rd International Workshop on Geographic Information Extraction from Texts at the 47th European Conference on Information Retrieval. Lucca, Italy, Apr 06-10, 2025. PDF
A Geoparsing Pipeline for Multilingual Social Media Posts from Ukraine.
GeoExT @ECIR 2025 - 3rd International Workshop on Geographic Information Extraction from Texts at the 47th European Conference on Information Retrieval. Lucca, Italy, Apr 06-10, 2025. PDF
[262]
N. Santhanam • H. E. Kim • D. Rügamer • A. Bender • S. Muthers • C. G. Cho • A. Alonso • K. Szabo • F.-S. Centner • H. Wenz • T. Ganslandt • M. Platten • C. Groden • M. Neumaier • F. Siegel • M. E. Maros
Machine learning-based forecasting of daily acute ischemic stroke admissions using weather data.
npj Digital Medicine 8.225. Apr. 2025. DOI
Machine learning-based forecasting of daily acute ischemic stroke admissions using weather data.
npj Digital Medicine 8.225. Apr. 2025. DOI
[261]
L. Bothmann • S. Dandl • J. M. Alvarez • P. A. Boustani • B. Bischl
Privilege Scores for Fairness-Aware ML.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available.
Privilege Scores for Fairness-Aware ML.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available.
[260]
L. Zumeta-Olaskoaga • A. Bender • D.-J. Lee
Flexible modelling of time-varying exposures in event history analysis.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available. DOI
Flexible modelling of time-varying exposures in event history analysis.
DAGStat 2025 - 7th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik. Berlin, Germany, Mar 24-28, 2025. Poster presentation. Full paper available. DOI
[259]
L. Zumeta-Olaskoaga • A. Bender • D.-J. Lee
Flexible modelling of time-varying exposures and recurrent events to analyse training load effects in team sports injuries.
Journal of the Royal Statistical Society. Series C (Applied Statistics) 74.2. Mar. 2025. DOI
Flexible modelling of time-varying exposures and recurrent events to analyse training load effects in team sports injuries.
Journal of the Royal Statistical Society. Series C (Applied Statistics) 74.2. Mar. 2025. DOI
[258]
R. Hornung • M. Nalenz • L. Schneider • A. Bender • L. Bothmann • F. Dumpert • B. Bischl • T. Augustin • A.-L. Boulesteix
Evaluating Machine Learning Models in Non-Standard Settings: An Overview and New Findings.
Statistical Science. Mar. 2025. To be published. Preprint available. URL
Evaluating Machine Learning Models in Non-Standard Settings: An Overview and New Findings.
Statistical Science. Mar. 2025. To be published. Preprint available. URL
[257]
A. Wuttke • M. Aßenmacher • C. Klamm • M. Lang • Q. Würschinger • F. Kreuter
AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers.
Preprint (Mar. 2025).
AI Conversational Interviewing: Transforming Surveys with LLMs as Adaptive Interviewers.
Preprint (Mar. 2025).
[256]
L. Burk • A. Bender • M. N. Wright
High-Dimensional Variable Selection With Competing Events Using Cooperative Penalized Regression.
Biometrical Journal 67.1. Feb. 2025. DOI
High-Dimensional Variable Selection With Competing Events Using Cooperative Penalized Regression.
Biometrical Journal 67.1. Feb. 2025. DOI
[255]
J. Rodemann • E. Garces Arias • C. Luther • C. Jansen • T. Augustin
A Statistical Case Against Empirical Human-AI Alignment.
Preprint (Feb. 2025).
A Statistical Case Against Empirical Human-AI Alignment.
Preprint (Feb. 2025).
[254]
M. Surner • A. Khelil • L. Bothmann
Invariance Pair-Guided Learning: Enhancing Robustness in Neural Networks.
Preprint (Feb. 2025).
Invariance Pair-Guided Learning: Enhancing Robustness in Neural Networks.
Preprint (Feb. 2025).
[253]
E. Garces Arias • M. Li • C. Heumann • M. Aßenmacher
Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation.
COLING 2025 - The 31st International Conference on Computational Linguistics. Abu Dhabi, United Arab Emirates, Jan 19-24, 2025. URL
Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation.
COLING 2025 - The 31st International Conference on Computational Linguistics. Abu Dhabi, United Arab Emirates, Jan 19-24, 2025. URL
[252]
L. Bothmann • K. Peters
Fairness von KI – ein Brückenschlag zwischen Philosophie und Maschinellem Lernen.
Grenzen Künstlicher Intelligenz. Jan. 2025. DOI
Fairness von KI – ein Brückenschlag zwischen Philosophie und Maschinellem Lernen.
Grenzen Künstlicher Intelligenz. Jan. 2025. DOI
[251]
H. Schulz-Kümpel • S. Fischer • T. Nagler • A.-L. Boulesteix • B. Bischl • R. Hornung
Constructing Confidence Intervals for 'the' Generalization Error – a Comprehensive Benchmark Study.
Journal of Data-centric Machine Learning Research 2.6. Jan. 2025. To be published. Preprint available. URL
Constructing Confidence Intervals for 'the' Generalization Error – a Comprehensive Benchmark Study.
Journal of Data-centric Machine Learning Research 2.6. Jan. 2025. To be published. Preprint available. URL
[250]
T. Weber • J. Dexl • D. Rügamer • M. Ingrisch
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition.
Radiology: Artificial Intelligence 7.2. Jan. 2025. DOI
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition.
Radiology: Artificial Intelligence 7.2. Jan. 2025. DOI
2024
[249]
Y. Zhang • Y. Li • X. Wang • Q. Shen • B. Plank • B. Bischl • M. Rezaei • K. Kawaguchi
FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models.
Compression Workshop @NeurIPS 2024 - Workshop on Machine Learning and Compression at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL
FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models.
Compression Workshop @NeurIPS 2024 - Workshop on Machine Learning and Compression at the 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL
[248]
T. Nagler • L. Schneider • B. Bischl • M. Feurer
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL GitHub
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization.
NeurIPS 2024 - 38th Conference on Neural Information Processing Systems. Vancouver, Canada, Dec 10-15, 2024. URL GitHub
[247]
J. Herbinger • M. N. Wright • T. Nagler • B. Bischl • G. Casalicchio
Decomposing Global Feature Effects Based on Feature Interactions.
Journal of Machine Learning Research 25.381. Dec. 2024. URL
Decomposing Global Feature Effects Based on Feature Interactions.
Journal of Machine Learning Research 25.381. Dec. 2024. URL
[246]
E. Garces Arias • J. Rodemann • M. Li • C. Heumann • M. Aßenmacher
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.
Findings @EMNLP 2024 - Findings of the Conference on Empirical Methods in Natural Language Processing. Miami, FL, USA, Nov 12-16, 2024. DOI
[245]
Y. Li • Y. Zhang • K. Kawaguchi • A. Khakzar • B. Bischl • M. Rezaei
A Dual-Perspective Approach to Evaluating Feature Attribution Methods.
Transactions on Machine Learning Research. Nov. 2024. URL
A Dual-Perspective Approach to Evaluating Feature Attribution Methods.
Transactions on Machine Learning Research. Nov. 2024. URL
[244]
J. Nam • I. Chalkidis • M. Rezaei
Hyperbolic Contrastive Learning for Document Representations – A Multi-View Approach with Paragraph-level Similarities.
ECAI 2024 - 27th European Conference on Artificial Intelligence. Santiago de Compostela, Spain, Oct 19-24, 2024. DOI
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
[243]
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
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
[242]
T. Pielok • B. Bischl • D. Rügamer
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent.
Preprint (Oct. 2024).
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent.
Preprint (Oct. 2024).
[241]
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
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
[240]
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
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
[239]
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
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
[238]
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
Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach.
Data Mining and Knowledge Discovery 38. Sep. 2024. DOI
[237]
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
Energy Expenditure Prediction in Preschool Children: A Machine Learning Approach Using Accelerometry and External Validation.
Physiological Measurement 45.9. Sep. 2024. DOI
[236]
A. Stephan • D. Zhu • M. Aßenmacher • X. Shen • B. Roth
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks.
Preprint (Sep. 2024).
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks.
Preprint (Sep. 2024).
[235]
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
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
[234]
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
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
[233]
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
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
[232]
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
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
[231]
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
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
[230]
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
Distributed non-disclosive validation of predictive models by a modified ROC-GLM.
BMC Medical Research Methodology 24.190. Aug. 2024. DOI
[229]
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
Predicting T cell receptor functionality against mutant epitopes.
Cell Genomics 4.9. Aug. 2024. DOI
[228]
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
Automatische ICD-10-Codierung.
Die Radiologie 64. Aug. 2024. DOI
[227]
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
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
[226]
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
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
[225]
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
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
[224]
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
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
[223]
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
Position: Embracing Negative Results in Machine Learning.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL
[222]
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
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
[221]
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
Generalizing orthogonalization for models with non-linearities.
ICML 2024 - 41st International Conference on Machine Learning. Vienna, Austria, Jul 21-27, 2024. URL
[220]
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
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
[219]
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
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
[218]
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
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
[217]
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
Interpretable Machine Learning for TabPFN.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI GitHub
[216]
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
Algorithm-Agnostic Feature Attributions for Clustering.
xAI 2024 - 2nd World Conference on Explainable Artificial Intelligence. Valletta, Malta, Jul 17-19, 2024. DOI
[215]
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.
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.
[214]
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
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
[213]
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
Label-wise Aleatoric and Epistemic Uncertainty Quantification.
UAI 2024 - 40th Conference on Uncertainty in Artificial Intelligence. Barcelona, Spain, Jul 16-18, 2024. URL
[212]
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
Flexible additive models for multi-event survival analysis.
IWSM 2024 - 38th International Workshop on Statistical Modelling. Durham, UK, Jul 14-19, 2024. PDF
[211]
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. GitHub
mlr3summary: Concise and interpretable summaries for machine learning models.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-22, 2024. GitHub
[210]
S. Fischer • M. Binder
mlr3torch - Deep Learning in R.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-22, 2024. GitHub
mlr3torch - Deep Learning in R.
useR! 2024 - International R User Conference. Salzburg, Austria, Jul 08-22, 2024. GitHub
[209]
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
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
[208]
F. Karl • J. Thomas • J. Elstner • R. Gross • B. Bischl
Automated Machine Learning.
Unlocking Artificial Intelligence. Jul. 2024. DOI
Automated Machine Learning.
Unlocking Artificial Intelligence. Jul. 2024. DOI
[207]
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
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
[206]
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
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
[205]
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
Recurrent events analysis with piece-wise exponential additive mixed models.
Statistical Modelling 24.3. Jun. 2024. DOI
[204]
B. Felderer • L. Repke • W. Weber • J. Schweisthal • L. Bothmann
Predicting the Validity and Reliability of Survey Questions.
Preprint (Jun. 2024). DOI
Predicting the Validity and Reliability of Survey Questions.
Preprint (Jun. 2024). DOI
[203]
E. Dorigatti
Cancer immunotherapy design and analysis through discrete optimization, positive-unlabeled learning, and semi-structured regression models.
Dissertation LMU München. May. 2024. DOI
Cancer immunotherapy design and analysis through discrete optimization, positive-unlabeled learning, and semi-structured regression models.
Dissertation LMU München. May. 2024. DOI
[202]
C. A. Scholbeck
Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations.
Dissertation LMU München. May. 2024. DOI
Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations.
Dissertation LMU München. May. 2024. DOI
[201]
K. Röck
Stochastic processes as surrogate models for dynamical systems in magnetic confinement fusion.
Dissertation LMU München. May. 2024. DOI
Stochastic processes as surrogate models for dynamical systems in magnetic confinement fusion.
Dissertation LMU München. May. 2024. DOI
[200]
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
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
[199]
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
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
[198]
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
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
[197]
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
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports.
European Radiology 34. May. 2024. DOI
[196]
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
From Embeddings to Explainability: A Tutorial on Transformer-Based Text Analysis for Social and Behavioral Scientists.
Preprint (May. 2024). DOI
[195]
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
Optimized model architectures for deep learning on genomic data.
Communications Biology 7.1. Apr. 2024. DOI
[194]
V. Gkolemis • C. Diou • E. Ntoutsi • T. Dalamagas • B. Bischl • J. Herbinger • G. Casalicchio
Effector: A Python package for regional explanations.
Preprint (Apr. 2024). GitHub
Effector: A Python package for regional explanations.
Preprint (Apr. 2024). GitHub
[193]
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
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
[192]
S. Dandl • C. Haslinger • T. Hothorn • H. Seibold • E. Sverdrup • S. Wager • A. Zeileis
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Annals of Applied Statistics 18.1. Mar. 2024. DOI
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Annals of Applied Statistics 18.1. Mar. 2024. DOI
[191]
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
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
[190]
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
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
[189]
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
Strategies to optimise machine learning classification performance when using biomechanical features.
Journal of Biomechanics 165. Mar. 2024. DOI
[188]
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
Heterogeneous treatment effect estimation for observational data using model-based forests.
Statistical Methods in Medical Research 33.3. Mar. 2024. DOI
[187]
A. Reuter • A. Thielmann • C. Weisser • S. F. Fischer • B. Säfken
GPTopic: Dynamic and Interactive Topic Representations.
Preprint (Mar. 2024). GitHub
GPTopic: Dynamic and Interactive Topic Representations.
Preprint (Mar. 2024). GitHub
[186]
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
Deep learning for survival analysis: a review.
Artificial Intelligence Review 57.65. Feb. 2024. DOI
[185]
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
Marginal Effects for Non-Linear Prediction Functions.
Data Mining and Knowledge Discovery 38. Feb. 2024. DOI
[184]
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
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.
Journal of Artificial Intelligence Research 79. Feb. 2024. DOI
[183]
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
AMLB: an AutoML Benchmark.
Journal of Machine Learning Research 25.101. Feb. 2024. URL
[182]
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
Privacy-Preserving and Lossless Distributed Estimation of High-Dimensional Generalized Additive Mixed Models.
Statistics and Computing 34.31. Feb. 2024. DOI
[181]
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
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
[180]
B. Bischl • R. Sonabend • L. Kotthoff • M. Lang
Applied Machine Learning Using mlr3 in R.
American Statistician 79.2. Jan. 2024. DOI
Applied Machine Learning Using mlr3 in R.
American Statistician 79.2. Jan. 2024. DOI
[179]
G. Casalicchio • L. Burk
Evaluation and Benchmarking.
Applied Machine Learning Using mlr3 in R I.3. Jan. 2024. DOI
Evaluation and Benchmarking.
Applied Machine Learning Using mlr3 in R I.3. Jan. 2024. DOI
[178]
M. Becker • L. Schneider • S. Fischer
Hyperparameter Optimization.
Applied Machine Learning Using mlr3 in R II.4. Jan. 2024. DOI
Hyperparameter Optimization.
Applied Machine Learning Using mlr3 in R II.4. Jan. 2024. DOI
[177]
L. Schneider • M. Becker
Advanced Tuning Methods and Black Box Optimization.
Applied Machine Learning Using mlr3 in R II.5. Jan. 2024. DOI
Advanced Tuning Methods and Black Box Optimization.
Applied Machine Learning Using mlr3 in R II.5. Jan. 2024. DOI
[176]
M. Binder • F. Pfisterer
Sequential Pipelines.
Applied Machine Learning Using mlr3 in R II.7. Jan. 2024. DOI
Sequential Pipelines.
Applied Machine Learning Using mlr3 in R II.7. Jan. 2024. DOI
[175]
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
Non-sequential Pipelines and Tuning.
Applied Machine Learning Using mlr3 in R II.8. Jan. 2024. DOI
[174]
M. Lang • S. F. Fischer • R. Sonabend
Advanced Technical Aspects of mlr3.
Applied Machine Learning Using mlr3 in R IV.10. Jan. 2024. DOI
Advanced Technical Aspects of mlr3.
Applied Machine Learning Using mlr3 in R IV.10. Jan. 2024. DOI
[173]
S. Fischer • M. Lang • M. Becker
Large-Scale Benchmarking.
Applied Machine Learning Using mlr3 in R IV.11. Jan. 2024. DOI
Large-Scale Benchmarking.
Applied Machine Learning Using mlr3 in R IV.11. Jan. 2024. DOI
[172]
S. Dandl • P. Biecek • G. Casalicchio • M. N. Wright
Model Interpretation.
Applied Machine Learning Using mlr3 in R IV.12. Jan. 2024. DOI
Model Interpretation.
Applied Machine Learning Using mlr3 in R IV.12. Jan. 2024. DOI
2023
[171]
J. Goschenhofer
Reducing the effort for data annotation: contributions to weakly supervised deep learning.
Dissertation LMU München. Dec. 2023. DOI
Reducing the effort for data annotation: contributions to weakly supervised deep learning.
Dissertation LMU München. Dec. 2023. DOI
[170]
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
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
[169]
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
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
[168]
S. Dandl
Causality concepts in machine learning: heterogeneous treatment effect estimation with machine learning and model interpretation with counterfactual and semi-factual explanations.
Dissertation LMU München. Dec. 2023. DOI
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
[167]
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
Automatic transcription of handwritten Old Occitan language.
EMNLP 2023 - Conference on Empirical Methods in Natural Language Processing. Singapore, Dec 06-10, 2023. DOI
[166]
J. Herbinger
On grouping and partitioning approaches in interpretable machine learning.
Dissertation LMU München. Dec. 2023. DOI
On grouping and partitioning approaches in interpretable machine learning.
Dissertation LMU München. Dec. 2023. DOI
[165]
F. Karl • T. Pielok • J. Moosbauer • F. Pfisterer • S. Coors • M. Binder • L. Schneider • J. Thomas • J. Richter • M. Lang • E. C. Garrido-Merchán • J. Branke • B. Bischl
Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview.
ACM Transactions on Evolutionary Learning and Optimization 3.4. Dec. 2023. DOI
Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview.
ACM Transactions on Evolutionary Learning and Optimization 3.4. Dec. 2023. DOI
[164]
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
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
[163]
Y. Sale • P. Hofman • L. Wimmer • E. Hüllermeier • T. Nagler
Second-Order Uncertainty Quantification: Variance-Based Measures.
Preprint (Dec. 2023).
Second-Order Uncertainty Quantification: Variance-Based Measures.
Preprint (Dec. 2023).
[162]
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).
Position Paper: Bridging the Gap Between Machine Learning and Sensitivity Analysis.
Preprint (Dec. 2023).
[161]
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
Mixture of Experts Distributional Regression: Implementation Using Robust Estimation with Adaptive First-order Methods.
Advances in Statistical Analysis. Nov. 2023. DOI
[160]
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
Automated wildlife image classification: An active learning tool for ecological applications.
Ecological Informatics 77. Nov. 2023. DOI
[159]
T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings.
Preprint (Nov. 2023).
Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings.
Preprint (Nov. 2023).
[158]
G. König
If interpretability is the answer, what is the question?: a causal perspective.
Dissertation LMU München. Oct. 2023. DOI
If interpretability is the answer, what is the question?: a causal perspective.
Dissertation LMU München. Oct. 2023. DOI
[157]
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
Deep Bregman divergence for self-supervised representations learning.
Computer Vision and Image Understanding 235.103801. Oct. 2023. DOI
[156]
I. Ziegler • B. Ma • B. Bischl • E. Dorigatti • B. Schubert
Proteasomal cleavage prediction: state-of-the-art and future directions.
Preprint (Oct. 2023). DOI GitHub
Proteasomal cleavage prediction: state-of-the-art and future directions.
Preprint (Oct. 2023). DOI GitHub
[155]
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
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
[154]
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
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
[153]
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
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
[152]
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
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
[151]
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
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
[150]
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
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
[149]
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
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
[148]
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
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
[147]
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
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
[146]
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
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
[145]
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
Symbolic Explanations for Hyperparameter Optimization.
AutoML 2023 - International Conference on Automated Machine Learning. Berlin, Germany, Sep 12-15, 2023. URL
[144]
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
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
[143]
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
A self-supervised deep learning method for data-efficient training in genomics.
Communications Biology 6.928. Sep. 2023. DOI
[142]
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
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
[141]
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
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
[140]
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
Auxiliary Cross-Modal Representation Learning With Triplet Loss Functions for Online Handwriting Recognition.
IEEE Access 11. Aug. 2023. DOI
[139]
F. Pfisterer • S. Wei • S. Vollmer • M. Lang • B. Bischl
Fairness Audits and Debiasing Using mlr3fairness.
The R Journal 15.1. Aug. 2023. DOI
Fairness Audits and Debiasing Using mlr3fairness.
The R Journal 15.1. Aug. 2023. DOI
[138]
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
Approximately Bayes-optimal pseudo-label selection.
UAI 2023 - 39th Conference on Uncertainty in Artificial Intelligence. Pittsburgh, PA, USA, Jul 31-Aug 03, 2023. URL
[137]
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
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
[136]
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
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
[135]
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
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
[134]
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
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
[133]
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
Sparse Modality Regression.
IWSM 2023 - 37th International Workshop on Statistical Modelling. Dortmund, Germany, Jul 17-21, 2023. Best Paper Award. PDF
[132]
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
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
[131]
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
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
[130]
M. Aßenmacher • N. Sauter • C. Heumann
Classifying multilingual party manifestos: Domain transfer across country, time, and genre.
Preprint (Jul. 2023).
Classifying multilingual party manifestos: Domain transfer across country, time, and genre.
Preprint (Jul. 2023).
[129]
C. Kolb • C. L. Müller • B. Bischl • D. Rügamer
Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization.
Preprint (Jul. 2023).
Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization.
Preprint (Jul. 2023).
[128]
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
Structured Verification of Machine Learning Models in Industrial Settings.
Big Data 11.3. Jun. 2023. DOI
[127]
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
Self-supervised Learning and Self-labeling Framework for Glaucoma Detection.
Investigative Ophthalmology and Visual Science 64.8. Jun. 2023. URL
[126]
J. Moosbauer
Towards explainable automated machine learning.
Dissertation LMU München. May. 2023. DOI
Towards explainable automated machine learning.
Dissertation LMU München. May. 2023. DOI
[125]
T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis.
PAKDD 2023 - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining. Osaka, Japan, May 25-28, 2023. DOI
[124]
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
Dependent state space Student-t processes for imputation and data augmentation in plasma diagnostics.
Contributions to Plasma Physics 63.5-6. May. 2023. DOI
[123]
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
Approximate Bayesian Inference with Stein Functional Variational Gradient Descent.
ICLR 2023 - 11th International Conference on Learning Representations. Kigali, Rwanda, May 01-05, 2023. URL
[122]
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
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
[121]
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
Efficient SAGE Estimation via Causal Structure Learning.
AISTATS 2023 - 26th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, Apr 25-27, 2023. URL
[120]
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
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
[119]
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
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization.
Journal of Computational and Graphical Statistics 32.2. Apr. 2023. DOI
[118]
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
A geometric framework for outlier detection in high-dimensional data.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery e1491. Apr. 2023. DOI
[117]
S. Dandl • A. Hofheinz • M. Binder • B. Bischl • G. Casalicchio
counterfactuals: An R Package for Counterfactual Explanation Methods.
Preprint (Apr. 2023).
counterfactuals: An R Package for Counterfactual Explanation Methods.
Preprint (Apr. 2023).
[116]
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
Modern approaches for component-wise boosting: Automation, efficiency, and distributed computing with application to the medical domain.
Dissertation LMU München. Mar. 2023. DOI
[115]
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.
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.
[114]
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
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13.2. Mar. 2023. DOI
[113]
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
Improvement-focused causal recourse (ICR).
AAAI 2023 - 37th Conference on Artificial Intelligence. Washington, DC, USA, Feb 07-14, 2023. DOI
[112]
D. Rügamer • C. Kolb • N. Klein
Semi-Structured Distributional Regression.
American Statistician. Feb. 2023. DOI
Semi-Structured Distributional Regression.
American Statistician. Feb. 2023. DOI
[111]
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
dsBinVal: Conducting distributed ROC analysis using DataSHIELD.
The Journal of Open Source Software 8.82. Feb. 2023. DOI
2022
[110]
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
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
[109]
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
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
[108]
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
Challenges in Interpreting Epidemiological Surveillance Data – Experiences from Germany.
Journal of Computational and Graphical Statistics 32.3. Dec. 2022. DOI
[107]
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
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
[106]
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
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
[105]
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
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
[104]
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
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
[103]
F. Pfisterer
Democratizing machine learning: contributions in AutoML and fairness.
Dissertation LMU München. Oct. 2022. DOI
Democratizing machine learning: contributions in AutoML and fairness.
Dissertation LMU München. Oct. 2022. DOI
[102]
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
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
[101]
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
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers.
IEEE Transactions on Evolutionary Computation 26.6. Oct. 2022. DOI
[100]
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
Data augmentation for disruption prediction via robust surrogate models.
Journal of Plasma Physics 88.5. Oct. 2022. DOI
[99]
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
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
[98]
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
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
[97]
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
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
[96]
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
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
[95]
R. Sonabend • A. Bender • S. Vollmer
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.
Bioinformatics 38.17. Sep. 2022. DOI GitHub
Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.
Bioinformatics 38.17. Sep. 2022. DOI GitHub
[94]
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
Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar.
Remote Sensing 14.18. Sep. 2022. DOI
[93]
E. Dorigatti • B. Bischl • B. Schubert
Improved proteasomal cleavage prediction with positive-unlabeled learning.
Preprint (Sep. 2022).
Improved proteasomal cleavage prediction with positive-unlabeled learning.
Preprint (Sep. 2022).
[92]
E. Dorigatti • J. Schweisthal • B. Bischl • M. Rezaei
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision.
Preprint (Sep. 2022). GitHub
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision.
Preprint (Sep. 2022). GitHub
[91]
C. A. Scholbeck • H. Funk • G. Casalicchio
Algorithm-Agnostic Interpretations for Clustering.
Preprint (Sep. 2022).
Algorithm-Agnostic Interpretations for Clustering.
Preprint (Sep. 2022).
[90]
S.-F. Zheng • J. Nam • E. Dorigatti • B. Bischl • S. Azizi • M. Rezaei
Joint Debiased Representation and Image Clustering Learning with Self-Supervision.
Preprint (Sep. 2022). GitHub
Joint Debiased Representation and Image Clustering Learning with Self-Supervision.
Preprint (Sep. 2022). GitHub
[89]
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.
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.
[88]
F. Ott • N. L. Raichur • D. Rügamer • T. Feigl • H. Neumann • B. Bischl • C. Mutschler
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression.
Preprint (Aug. 2022).
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression.
Preprint (Aug. 2022).
[87]
L. Schneider • L. Schäpermeier • R. Prager • B. Bischl • H. Trautmann • P. Kerschke
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
Preprint (Aug. 2022).
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.
Preprint (Aug. 2022).
[86]
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
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
[85]
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
Tackling neural architecture search with quality diversity optimization.
AutoML 2022 - International Conference on Automated Machine Learning. Baltimore, MD, USA, Jul 25-27, 2022. URL
[84]
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
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
[83]
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.
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.
[82]
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
Multi-Objective Counterfactual Fairness.
GECCO 2022 - Genetic and Evolutionary Computation Conference. Boston, MA, USA, Jul 09-13, 2022. DOI
[81]
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
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
[80]
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
Grouped Feature Importance and Combined Features Effect Plot.
Data Mining and Knowledge Discovery 36. Jun. 2022. DOI
[79]
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
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
[78]
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
REPID: Regional Effect Plots with implicit Interaction Detection.
AISTATS 2022 - 25th International Conference on Artificial Intelligence and Statistics. Virtual, Mar 28-30, 2022. URL
[77]
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
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features.
Computational Statistics 37. Mar. 2022. DOI
[76]
C. Fritz • E. Dorigatti • D. Rügamer
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
Scientific Reports 12.3930. Mar. 2022. DOI
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany.
Scientific Reports 12.3930. Mar. 2022. DOI
[75]
C. Sauer • M. Herrmann • C. Wiedemann • G. Casalicchio • A.-L. Boulesteix
Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12.2. Mar. 2022. DOI
Over-optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12.2. Mar. 2022. DOI
[74]
F. Ott • D. Rügamer • L. Heublein • B. Bischl • C. Mutschler
Cross-Modal Common Representation Learning with Triplet Loss Functions.
Preprint (Mar. 2022). DOI
Cross-Modal Common Representation Learning with Triplet Loss Functions.
Preprint (Mar. 2022). DOI
[73]
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
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
[72]
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
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
[71]
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
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
[70]
W. Hartl • P. Kopper • A. Bender • F. Scheipl • A. G. Day • G. Elke • H. Küchenhoff
Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models.
Critical Care 26.7. Jan. 2022. DOI
Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models.
Critical Care 26.7. Jan. 2022. DOI
[69]
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
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
[68]
E. Dorigatti • J. Goschenhofer • B. Schubert • M. Rezaei • B. Bischl
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection.
Preprint (Jan. 2022).
Positive-Unlabeled Learning with Uncertainty-aware Pseudo-label Selection.
Preprint (Jan. 2022).
2021
[67]
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.
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.
[66]
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
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
[65]
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
Explaining Hyperparameter Optimization via Partial Dependence Plots.
NeurIPS 2021 - 35th Conference on Neural Information Processing Systems. Virtual, Dec 06-14, 2021. URL GitHub
[64]
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
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
[63]
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
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
[62]
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
Machine learning for the educational sciences.
Review of Education 9.3. Nov. 2021. DOI
[61]
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
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
[60]
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.
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.
[59]
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
mlr3proba: An R Package for Machine Learning in Survival Analysis.
Bioinformatics 37.17. Sep. 2021. DOI
[58]
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). GitHub
Deep Variational Clustering Framework for Self-labeling of Large-scale Medical Images.
Preprint (Sep. 2021). GitHub
[57]
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
Bi-Centric Independent Validation of Outcome Prediction after Radioembolization of Primary and Secondary Liver Cancer.
Journal of Clinical Medicine 10.16. Aug. 2021. DOI
[56]
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
mcboost: Multi-Calibration Boosting for R.
The Journal of Open Source Software 6.64. Aug. 2021. DOI
[55]
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
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
[54]
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
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
[53]
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
Meta-Learning for Symbolic Hyperparameter Defaults.
GECCO 2021 - Genetic and Evolutionary Computation Conference. Lile, France, Jul 10-14, 2021. DOI
[52]
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
Learning Multiple Defaults for Machine Learning Algorithms.
GECCO 2021 - Genetic and Evolutionary Computation Conference. Lile, France, Jul 10-14, 2021. DOI
[51]
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
Predicting non-state terrorism worldwide.
Science Advances 7.31. Jul. 2021. DOI
[50]
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
mlr3pipelines - Flexible Machine Learning Pipelines in R.
Journal of Machine Learning Research 22.184. Jun. 2021. URL
[49]
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
A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses.
PLOS One 16.6. Jun. 2021. DOI
[48]
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).
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT).
Preprint (Jun. 2021).
[47]
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
Automated Online Experiment-Driven Adaptation--Mechanics and Cost Aspects.
IEEE Access 9. Apr. 2021. DOI
[46]
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
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
[45]
J. Goschenhofer • R. Hvingelby • D. Rügamer • J. Thomas • M. Wagner • B. Bischl
Deep Semi-Supervised Learning for Time Series Classification.
Preprint (Feb. 2021).
Deep Semi-Supervised Learning for Time Series Classification.
Preprint (Feb. 2021).
[44]
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
Relative Feature Importance.
ICPR 2020 - 25th International Conference on Pattern Recognition. Virtual - Milano, Italy, Jan 10-15, 2021. DOI
[43]
M. Becker • S. Gruber • J. Richter • J. Moosbauer • B. Bischl
mlr3hyperband: Hyperband for 'mlr3'.
2021. URL GitHub
mlr3hyperband: Hyperband for 'mlr3'.
2021. URL GitHub
[42]
M. Becker • M. Lang • J. Richter • B. Bischl • D. Schalk
mlr3tuning: Tuning for 'mlr3'.
2021. URL GitHub
mlr3tuning: Tuning for 'mlr3'.
2021. URL GitHub
[41]
M. Becker • J. Richter • M. Lang • B. Bischl • M. Binder
bbotk: Black-Box Optimization Toolkit.
2021. URL GitHub
bbotk: Black-Box Optimization Toolkit.
2021. URL GitHub
[40]
[39]
[38]
M. Lang • B. Bischl • J. Richter • X. Sun • M. Binder
paradox: Define and Work with Parameter Spaces for Complex Algorithms.
2021. URL GitHub
paradox: Define and Work with Parameter Spaces for Complex Algorithms.
2021. URL GitHub
[37]
D. Rügamer • F. Pfisterer • P. Baumann
deepregression: Fitting Semi-Structured Deep Distributional Regression in R.
2021. URL
deepregression: Fitting Semi-Structured Deep Distributional Regression in R.
2021. URL
[36]
2020
[35]
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).
Debiasing classifiers: is reality at variance with expectation?
Preprint (Nov. 2020).
[34]
D. Rügamer • F. Pfisterer • B. Bischl
Neural Mixture Distributional Regression.
Preprint (Oct. 2020).
Neural Mixture Distributional Regression.
Preprint (Oct. 2020).
[33]
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
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
[32]
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
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
[31]
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
Multi-Objective Counterfactual Explanations.
PPSN 2020 - 16th International Conference on Parallel Problem Solving from Nature. Leiden, Netherlands, Sep 05-09, 2020. DOI
[30]
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
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
[29]
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
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
[28]
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
Multi-Objective Hyperparameter Tuning and Feature Selection Using Filter Ensembles.
GECCO 2020 - Genetic and Evolutionary Computation Conference. Cancun, Mexico, Jul 08-12, 2020. DOI
[27]
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
Improved outcome prediction across data sources through robust parameter tuning.
Journal of Classification 38. Jul. 2020. DOI
[26]
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
Predicting personality from patterns of behavior collected with smartphones.
Proceedings of the National Academy of Sciences 117.30. Jul. 2020. DOI
[25]
[24]
M. Binder • F. Pfisterer • L. Schneider • B. Bischl • M. Lang • S. Dandl
mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'.
2020. URL GitHub
mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'.
2020. URL GitHub
[23]
[22]
[21]
M. Lang • Q. Au • S. Coors • P. Schratz
mlr3learners: Recommended Learners for 'mlr3'.
2020. URL GitHub
mlr3learners: Recommended Learners for 'mlr3'.
2020. URL GitHub
[20]
[19]
[18]
P. Schratz • M. Lang • B. Bischl • M. Binder
mlr3filters: Filter Based Feature Selection for 'mlr3'.
2020. URL GitHub
mlr3filters: Filter Based Feature Selection for 'mlr3'.
2020. URL GitHub
[17]
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
mlr3proba: Probabilistic Supervised Learning for 'mlr3'. R package version 0.2.6.
2020. DOI URL
[16]
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
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
2019
[15]
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
mlr3: A modern object-oriented machine learning framework in R.
The Journal of Open Source Software 4.44. Dec. 2019. DOI
[14]
M. Binder • J. Moosbauer • J. Thomas • B. Bischl
Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles.
Preprint (Dec. 2019).
Multi-Objective Hyperparameter Tuning and Feature Selection using Filter Ensembles.
Preprint (Dec. 2019).
[13]
F. Pfisterer • L. Beggel • X. Sun • F. Scheipl • B. Bischl
Benchmarking time series classification -- Functional data vs machine learning approaches.
Preprint (Nov. 2019).
Benchmarking time series classification -- Functional data vs machine learning approaches.
Preprint (Nov. 2019).
[12]
[11]
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.
A Causal Perspective on Challenges for AI in Precision Medicine.
PMBC 2019 - 2nd International Congress on Precision Medicine. Munich, Germany, Oct 14-15, 2019.
[10]
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
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
[9]
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
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
[8]
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
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
[7]
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
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
[6]
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.
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.
[5]
J. Thomas
Gradient boosting in automatic machine learning: feature selection and hyperparameter optimization.
Dissertation LMU München. Apr. 2019. DOI
Gradient boosting in automatic machine learning: feature selection and hyperparameter optimization.
Dissertation LMU München. Apr. 2019. DOI
[4]
Q. Au • D. Schalk • G. Casalicchio • R. Schoedel • C. Stachl • B. Bischl
Component-Wise Boosting of Targets for Multi-Output Prediction.
Preprint (Apr. 2019).
Component-Wise Boosting of Targets for Multi-Output Prediction.
Preprint (Apr. 2019).
[3]
G. Casalicchio
On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models.
Dissertation LMU München. Mar. 2019. DOI
On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models.
Dissertation LMU München. Mar. 2019. DOI
[2]
P. Probst • A.-L. Boulesteix • B. Bischl
Tunability: Importance of Hyperparameters of Machine Learning Algorithms.
Journal of Machine Learning Research 20. Mar. 2019. PDF
Tunability: Importance of Hyperparameters of Machine Learning Algorithms.
Journal of Machine Learning Research 20. Mar. 2019. PDF
[1]
M. Binder • S. Dandl • J. Moosbauer
mosmafs: Multi-Objective Simultaneous Model and Feature Selection. R package.
2019. GitHub
mosmafs: Multi-Objective Simultaneous Model and Feature Selection. R package.
2019. GitHub
©all images: LMU | TUM