Nagler, Thomas

13 publications

ICML 2025 Adjustment for Confounding Using Pre-Trained Representations Rickmer Schulte, David Rügamer, Thomas Nagler

ICLRW 2025 Adjustment for Confounding Using Pre-Trained Representations Rickmer Schulte, David Rügamer, Thomas Nagler

DMLR 2025 Constructing Confidence Intervals for “the” Generalization Error – A Comprehensive Benchmark Study Hannah Schulz-Kümpel, Sebastian Felix Fischer, Roman Hornung, Anne-Laure Boulesteix, Thomas Nagler, Bernd Bischl

UAI 2025 Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals Marcel Arpogaus, Thomas Kneib, Thomas Nagler, David Rügamer

ICLRW 2025 Uncertainty Quantification for Prior-Fitted Networks Using Martingale Posteriors Thomas Nagler, David Rügamer

AISTATS 2024 An Online Bootstrap for Time Series Nicolai Palm, Thomas Nagler

JMLR 2024 Decomposing Global Feature Effects Based on Feature Interactions Julia Herbinger, Marvin N. Wright, Thomas Nagler, Bernd Bischl, Giuseppe Casalicchio

ICML 2024 Generalizing Orthogonalization for Models with Non-Linearities David Rügamer, Chris Kolb, Tobias Weber, Lucas Kook, Thomas Nagler

UAI 2024 Label-Wise Aleatoric and Epistemic Uncertainty Quantification Yusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier

NeurIPS 2024 Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization Thomas Nagler, Lennart Schneider, Bernd Bischl, Matthias Feurer

NeurIPSW 2024 Towards Localization via Data Embedding for TabPFN Mykhailo Koshil, Thomas Nagler, Matthias Feurer, Katharina Eggensperger

UAI 2023 Approximately Bayes-Optimal Pseudo-Label Selection Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin

ICML 2023 Statistical Foundations of Prior-Data Fitted Networks Thomas Nagler