Bernd Bischl

Structured Credal Learning UAI 2026 Calibrating LLMs with Information-Theoretic Evidential Deep Learning ICLR 2025 Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries ICLR 2025 Efficient and Accurate Explanation Estimation with Distribution Compression ICLR 2025 Overtuning in Hyperparameter Optimization AutoML 2025 Revisiting Active Learning under (Human) Label Variation EMNLP 2025 Revisiting Unbiased Implicit Variational Inference ICML 2025 AMLB: an AutoML Benchmark JMLR 2024 Collaborative Development of Modular Open Source Educational Resources for Natural Language Processing ACL 2024 Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? ICML 2024 Constrained Probabilistic Mask Learning for Task-Specific Undersampled MRI Reconstruction WACV 2024 Decomposing Global Feature Effects Based on Feature Interactions JMLR 2024 Position: A Call to Action for a Human-Centered AutoML Paradigm ICML 2024 Position: Why We Must Rethink Empirical Research in Machine Learning ICML 2024 Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization ICLR 2024 Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization NeurIPS 2024 Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract) IJCAI 2024 Approximate Bayesian Inference with Stein Functional Variational Gradient Descent ICLR 2023 Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning ACL 2023 Frequentist Uncertainty Quantification in Semi-Structured Neural Networks AISTATS 2023 Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML AutoML 2023 Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? UAI 2023 Symbolic Explanations for Hyperparameter Optimization AutoML 2023 CC-Top: Constrained Clustering for Dynamic Topic Discovery EMNLP 2022 FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation NeurIPS 2022 Joint Classification and Trajectory Regression of Online Handwriting Using a Multi-Task Learning Approach WACV 2022 REPID: Regional Effect Plots with implicit Interaction Detection AISTATS 2022 Tackling Neural Architecture Search With Quality Diversity Optimization AutoML 2022 YAHPO Gym - An Efficient Multi-Objective Multi-Fidelity Benchmark for Hyperparameter Optimization AutoML 2022 Explaining Hyperparameter Optimization via Partial Dependence Plots NeurIPS 2021 mlr3pipelines - Flexible Machine Learning Pipelines in R JMLR 2021 Tunability: Importance of Hyperparameters of Machine Learning Algorithms JMLR 2019 mlr: Machine Learning in R JMLR 2016