Niklas Pfister

According to our database1, Niklas Pfister authored at least 14 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Invariant Policy Learning: A Causal Perspective.
IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Supervised learning and model analysis with compositional data.
PLoS Comput. Biol., 2023

Boosted Control Functions.
CoRR, 2023

Identifying Representations for Intervention Extrapolation.
CoRR, 2023

Effect-Invariant Mechanisms for Policy Generalization.
CoRR, 2023

2022
Interpreting tree ensemble machine learning models with endoR.
PLoS Comput. Biol., December, 2022

A Causal Framework for Distribution Generalization.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Identifiability of sparse causal effects using instrumental variables.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Exploiting Independent Instruments: Identification and Distribution Generalization.
Proceedings of the International Conference on Machine Learning, 2022

Causal Models for Dynamical Systems.
Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

2019
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise.
J. Mach. Learn. Res., 2019

2018
Identifying Causal Structure in Large-Scale Kinetic Systems.
CoRR, 2018

groupICA: Independent component analysis for grouped data.
CoRR, 2018


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