62 citations · 125 across the 26 of their papers we have counts for
27 papers
Linear Independent Component Analysis via Optimal Transport
Ashutosh Jha, Michel Besserve, Simon Buchholz
Linear Independent Component Analysis (ICA) recovers jointly independent source signals from their linear mixtures. To achieve this, classical ICA algorithms attempt to maximize no…
Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies
Armin Kekić, Jan Schneider, Dieter Büchler +2
Why do reinforcement learning (RL) policies fail or succeed? This is a challenging question due to the complex, high-dimensional nature of agent-environment interactions. In this w…
Controlling for discrete unmeasured confounding in nonlinear causal models
Patrick Burauel, Frederick Eberhardt, Michel Besserve
Unmeasured confounding is a major challenge for identifying causal relationships from non-experimental data. Here, we propose a method that can accommodate unmeasured discrete conf…
Independent Mechanism Analysis and the Manifold Hypothesis
Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen +2
Independent Mechanism Analysis (IMA) seeks to address non-identifiability in nonlinear Independent Component Analysis (ICA) by assuming that the Jacobian of the mixing function has…
Targeted Reduction of Causal Models
Armin Kekić, Bernhard Schölkopf, Michel Besserve
Why does a phenomenon occur? Addressing this question is central to most scientific inquiries and often relies on simulations of scientific models. As models become more intricate,…
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen, Michel Besserve, Liang Wendong +5
We study causal representation learning, the task of inferring latent causal variables and their causal relations from high-dimensional mixtures of the variables. Prior work relies…