Niklas Pfister

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Identically Distributed

Learning Models

Independent Component Analysis

Causal Structure

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

PLoS Comput. Biol.

J. Mach. Learn. Res.

Publications

Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Kumar Ravikumar, Niklas Pfister, Jonas Peters
Identifying Representations for Intervention Extrapolation. ICLR (2024)
Margherita Lazzaretto, Jonas Peters, Niklas Pfister
Invariant Subspace Decomposition. CoRR (2024)
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister
Invariant Policy Learning: A Causal Perspective. IEEE Trans. Pattern Anal. Mach. Intell. 45 (7) (2023)
Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister
Supervised learning and model analysis with compositional data. PLoS Comput. Biol. 19 (6) (2023)
Sorawit Saengkyongam, Niklas Pfister, Predrag V. Klasnja, Susan Murphy, Jonas Peters
Effect-Invariant Mechanisms for Policy Generalization. CoRR (2023)
Nicola Gnecco, Jonas Peters, Sebastian Engelke, Niklas Pfister
Boosted Control Functions. CoRR (2023)
Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Ravikumar, Niklas Pfister, Jonas Peters
Identifying Representations for Intervention Extrapolation. CoRR (2023)
Sorawit Saengkyongam, Leonard Henckel, Niklas Pfister, Jonas Peters
Exploiting Independent Instruments: Identification and Distribution Generalization. CoRR (2022)
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 (2022)
Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister
Supervised Learning and Model Analysis with Compositional Data. CoRR (2022)
Sorawit Saengkyongam, Leonard Henckel, Niklas Pfister, Jonas Peters
Exploiting Independent Instruments: Identification and Distribution Generalization. ICML (2022)
Albane Ruaud, Niklas Pfister, Ruth E. Ley, Nicholas D. Youngblut
Interpreting tree ensemble machine learning models with endoR. PLoS Comput. Biol. 18 (12) (2022)
Niklas Pfister, Jonas Peters
Identifiability of sparse causal effects using instrumental variables. UAI (2022)
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) (2022)
Sorawit Saengkyongam, Nikolaj Thams, Jonas Peters, Niklas Pfister
Invariant Policy Learning: A Causal Perspective. CoRR (2021)
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)
Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise. J. Mach. Learn. Res. 20 (2019)
Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
groupICA: Independent component analysis for grouped data. CoRR (2018)
Niklas Pfister, Stefan Bauer, Jonas Peters
Identifying Causal Structure in Large-Scale Kinetic Systems. CoRR (2018)