| 2025 | ICDM | TabFairGDT: A Fast Fair Tabular Data Generator Using Autoregressive Decision Trees. | Emmanouil Panagiotou, Benot Ronval, Arjun Roy, Ludwig Bothmann, Bernd Bischl, Siegfried Nijssen, Eirini Ntoutsi |
| 2025 | ICLR | Efficient and Accurate Explanation Estimation with Distribution Compression. | Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek |
| 2025 | ICLR | Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries. | Chris Kolb, Tobias Weber, Bernd Bischl, David Rgamer |
| 2025 | ICLR | Calibrating LLMs with Information-Theoretic Evidential Deep Learning. | Yawei Li, David Rgamer, Bernd Bischl, Mina Rezaei |
| 2025 | ICML | Revisiting Unbiased Implicit Variational Inference. | Tobias Pielok, Bernd Bischl, David Rgamer |
| 2025 | PAKDD | Preventing Sensitive Information Leakage via Post-hoc Orthogonalization with Application to Chest Radiograph Embeddings. | Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rgamer |
| 2024 | ICLR | Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization. | Amirhossein Vahidi, Simon Schoer, Lisa Wimmer, Yawei Li, Bernd Bischl, Eyke Hllermeier, Mina Rezaei |
| 2024 | ICML | Position: Why We Must Rethink Empirical Research in Machine Learning. | Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever, Matthias Feurer, David Rgamer, Eyke Hllermeier, Anne-Laure Boulesteix, Bernd Bischl |
| 2024 | ICML | Position: A Call to Action for a Human-Centered AutoML Paradigm. | Marius Lindauer, Florian Karl, Anne Klier, Julia Moosbauer, Alexander Tornede, Andreas Mller, Frank Hutter, Matthias Feurer, Bernd Bischl |
| 2024 | ICML | Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? | Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rgamer |
| 2024 | IJCAI | Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract). | Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Gnnemann, David Rgamer |
| 2024 | WACV | Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction. | Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rgamer |
| 2023 | ACL | Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning. | Daniel Saggau, Mina Rezaei, Bernd Bischl, Ilias Chalkidis |
| 2023 | AISTATS | Frequentist Uncertainty Quantification in Semi-Structured Neural Networks. | Emilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Rgamer |
| 2023 | CIBCB | Neural Architecture Search for Genomic Sequence Data. | Amadeu Scheppach, Hseyin Anil Gndz, Emilio Dorigatti, Philipp C. Mnch, Alice C. McHardy, Bernd Bischl, Mina Rezaei, Martin Binder |
| 2023 | FOGA | Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. | Raphael Patrick Prager, Konstantin Dietrich, Lennart Schneider, Lennart Schpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, Olaf Mersmann |
| 2023 | GECCO | Bayesian Optimization. | Ivo Couckuyt, Sebastian Rojas-Gonzalez, Jrgen Branke, Bernd Bischl |
| 2023 | GECCO | Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models. | Lennart Schneider, Bernd Bischl, Janek Thomas |
| 2023 | ICLR | Approximate Bayesian Inference with Stein Functional Variational Gradient Descent. | Tobias Pielok, Bernd Bischl, David Rgamer |
| 2023 | ICMLA | Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences. | Hseyin Anil Gndz, Sheetal Giri, Martin Binder, Bernd Bischl, Mina Rezaei |
| 2023 | IJCNN | ConstraintMatch for Semi-constrained Clustering. | Jann Goschenhofer, Bernd Bischl, Zsolt Kira |
| 2023 | IDA | Mind the Gap: Measuring Generalization Performance Across Multiple Objectives. | Matthias Feurer, Katharina Eggensperger, Edward Bergman, Florian Pfisterer, Bernd Bischl, Frank Hutter |
| 2023 | PAKDD | Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis. | Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rgamer |
| 2023 | UAI | Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? | Lisa Wimmer, Yusuf Sale, Paul Hofman, Bernd Bischl, Eyke Hllermeier |
| 2022 | AISTATS | REPID: Regional Effect Plots with implicit Interaction Detection. | Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio |
| 2022 | GECCO | Multi-objective counterfactual fairness. | Susanne Dandl, Florian Pfisterer, Bernd Bischl |
| 2022 | GECCO | A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. | Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl |
| 2022 | ICDM | Joint Debiased Representation Learning and Imbalanced Data Clustering. | Mina Rezaei, Emilio Dorigatti, David Rgamer, Bernd Bischl |
| 2022 | ICPR | Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition. | Felix Ott, David Rgamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler |
| 2022 | IJCAI | Uncertainty-aware Evaluation of Time-series Classification for Online Handwriting Recognition with Domain Shift. | Andreas Kla, Sven M. Lorenz, Martin W. Lauer-Schmaltz, David Rgamer, Bernd Bischl, Christopher Mutschler, Felix Ott |
| 2022 | MICCAI | Implicit Embeddings via GAN Inversion for High Resolution Chest Radiographs. | Tobias Weber, Michael Ingrisch, Bernd Bischl, David Rgamer |
| 2022 | PAKDD | DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis. | Philipp Kopper, Simon Wiegrebe, Bernd Bischl, Andreas Bender, David Rgamer |
| 2022 | PPSN | HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. | Lennart Schneider, Lennart Schpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke |
| 2022 | WACV | Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach. | Felix Ott, David Rgamer, Lucas Heublein, Bernd Bischl, Christopher Mutschler |
| 2021 | GECCO | Meta-learning for symbolic hyperparameter defaults. | Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren |
| 2021 | GECCO | Learning multiple defaults for machine learning algorithms. | Florian Pfisterer, Jan N. van Rijn, Philipp Probst, Andreas C. Mller, Bernd Bischl |
| 2021 | ICMLA | Deep Semi-supervised Learning for Time Series Classification. | Jann Goschenhofer, Rasmus Hvingelby, David Rgamer, Janek Thomas, Moritz Wagner, Bernd Bischl |
| 2020 | GECCO | Multi-objective hyperparameter tuning and feature selection using filter ensembles. | Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl |
| 2020 | ICML | General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models. | Christoph Molnar, Gunnar Knig, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, Bernd Bischl |
| 2020 | ICPR | Relative Feature Importance. | Gunnar Knig, Christoph Molnar, Bernd Bischl, Moritz Grosse-Wentrup |
| 2020 | PPSN | Multi-Objective Counterfactual Explanations. | Susanne Dandl, Christoph Molnar, Martin Binder, Bernd Bischl |
| 2018 | SoCS | A Regression-Based Methodology for Online Algorithm Selection. | Hans Degroote, Patrick De Causmaecker, Bernd Bischl, Lars Kotthoff |
| 2017 | EMO | First Investigations on Noisy Model-Based Multi-objective Optimization. | Daniel Horn, Melanie Dagge, Xudong Sun, Bernd Bischl |
| 2017 | GECCO | Evaluating random forest models for irace. | Leslie Prez Cceres, Bernd Bischl, Thomas Sttzle |
| 2015 | EMO | Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark. | Daniel Horn, Tobias Wagner, Dirk Biermann, Claus Weihs, Bernd Bischl |
| 2015 | GECCO | Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. | Jakob Bossek, Bernd Bischl, Tobias Wagner, Gnter Rudolph |
| 2015 | GECCO | The Impact of Initial Designs on the Performance of MATSuMoTo on the Noiseless BBOB-2015 Testbed: A Preliminary Study. | Dimo Brockhoff, Bernd Bischl, Tobias Wagner |
| 2015 | IJCNN | To tune or not to tune: Recommending when to adjust SVM hyper-parameters via meta-learning. | Rafael Gomes Mantovani, Andr Luis Debiaso Rossi, Joaquin Vanschoren, Bernd Bischl, Andr C. P. L. F. de Carvalho |
| 2015 | IJCNN | Effectiveness of Random Search in SVM hyper-parameter tuning. | Rafael Gomes Mantovani, Andr Luis Debiaso Rossi, Joaquin Vanschoren, Bernd Bischl, Andr C. P. L. F. de Carvalho |
| 2015 | KDD | Taking machine learning research online with OpenML. | Joaquin Vanschoren, Jan N. van Rijn, Bernd Bischl |
| 2013 | FOGA | A feature-based comparison of local search and the christofides algorithm for the travelling salesperson problem. | Samadhi Nallaperuma, Markus Wagner, Frank Neumann, Bernd Bischl, Olaf Mersmann, Heike Trautmann |
| 2012 | GECCO | Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. | Bernd Bischl, Olaf Mersmann, Heike Trautmann, Mike Preu |
| 2011 | GECCO | Exploratory landscape analysis. | Olaf Mersmann, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, Gnter Rudolph |
| 2010 | PPSN | Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation. | Bernd Bischl, Igor Vatolkin, Mike Preuss |