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2020 – today
- 2025
[i12]Niklas Pfister, Václav Volhejn, Manuel Knott, Santiago Arias, Julia Bazinska, Mykhailo Bichurin, Alan Commike, Janet Darling, Peter Dienes, Matthew Fiedler, David Haber, Matthias Kraft, Marco Lancini, Max Mathys, Damián Pascual-Ortiz, Jakub Podolak, Adrià Romero-López, Kyriacos Shiarlis, Andreas Signer, Zsolt Terek, Athanasios Theocharis, Daniel Timbrell, Samuel Trautwein, Samuel Watts, Yun-Han Wu, Mateo Rojas-Carulla:
Gandalf the Red: Adaptive Security for LLMs. CoRR abs/2501.07927 (2025)- 2024
- [j6]Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan A. Murphy, Jonas Peters:
Effect-Invariant Mechanisms for Policy Generalization. J. Mach. Learn. Res. 25: 34:1-34:36 (2024) - [c4]Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Kumar Ravikumar, Niklas Pfister, Jonas Peters:
Identifying Representations for Intervention Extrapolation. ICLR 2024 - [i11]Margherita Lazzaretto, Jonas Peters, Niklas Pfister:
Invariant Subspace Decomposition. CoRR abs/2404.09962 (2024) - [i10]Jinyang Liu, Tessa Steensgaard, Marvin N. Wright
, Niklas Pfister, Munir Hiabu:
Fast Estimation of Partial Dependence Functions using Trees. CoRR abs/2410.13448 (2024) - 2023
- [j5]Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister:
Invariant Policy Learning: A Causal Perspective. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8606-8620 (2023) - [j4]Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister:
Supervised learning and model analysis with compositional data. PLoS Comput. Biol. 19(6) (2023) - [i9]Sorawit Saengkyongam, Niklas Pfister, Predrag V. Klasnja, Susan A. Murphy, Jonas Peters:
Effect-Invariant Mechanisms for Policy Generalization. CoRR abs/2306.10983 (2023) - [i8]Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Ravikumar, Niklas Pfister, Jonas Peters:
Identifying Representations for Intervention Extrapolation. CoRR abs/2310.04295 (2023) - [i7]Nicola Gnecco, Jonas Peters, Sebastian Engelke, Niklas Pfister:
Boosted Control Functions. CoRR abs/2310.05805 (2023) - 2022
- [j3]Rune Christiansen, Niklas Pfister, Martin Emil Jakobsen, Nicola Gnecco, Jonas Peters:
A Causal Framework for Distribution Generalization. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6614-6630 (2022) - [j2]Albane Ruaud, Niklas Pfister, Ruth E. Ley, Nicholas D. Youngblut:
Interpreting tree ensemble machine learning models with endoR. PLoS Comput. Biol. 18(12): 1010714 (2022) - [c3]Sorawit Saengkyongam, Leonard Henckel, Niklas Pfister, Jonas Peters:
Exploiting Independent Instruments: Identification and Distribution Generalization. ICML 2022: 18935-18958 - [c2]Niklas Pfister, Jonas Peters:
Identifiability of sparse causal effects using instrumental variables. UAI 2022: 1613-1622 - [p1]Jonas Peters, Stefan Bauer, Niklas Pfister:
Causal Models for Dynamical Systems. Probabilistic and Causal Inference 2022: 671-690 - [i6]Sorawit Saengkyongam, Leonard Henckel, Niklas Pfister, Jonas Peters:
Exploiting Independent Instruments: Identification and Distribution Generalization. CoRR abs/2202.01864 (2022) - [i5]Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee, Dominik Baumann, Oliver Kroemer, Isabelle Guyon, Sebastian Trimpe, Jonas Peters, Niklas Pfister:
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning. CoRR abs/2202.06052 (2022) - [i4]Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister:
Supervised Learning and Model Analysis with Compositional Data. CoRR abs/2205.07271 (2022) - 2021
- [c1]Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee, Dominik Baumann, Oliver Kroemer, Isabelle Guyon, Sebastian Trimpe, Jonas Peters, Niklas Pfister:
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning. NeurIPS (Competition and Demos) 2021: 246-258 - [i3]Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister:
Invariant Policy Learning: A Causal Perspective. CoRR abs/2106.00808 (2021)
2010 – 2019
- 2019
- [j1]Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf:
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise. J. Mach. Learn. Res. 20: 147:1-147:50 (2019) - 2018
- [i2]Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf:
groupICA: Independent component analysis for grouped data. CoRR abs/1806.01094 (2018) - [i1]Niklas Pfister, Stefan Bauer, Jonas Peters:
Identifying Causal Structure in Large-Scale Kinetic Systems. CoRR abs/1810.11776 (2018)
Coauthor Index
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