3 papers
cs.LG2025
Algorithmic causal structure emerging through compression
Liang Wendong, Simon Buchholz, Bernhard Schölkopf
We explore the relationship between causality, symmetry, and compression. We build on and generalize the known connection between learning and compression to a setting where causal…
stat.ML2023
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…
stat.ML2023
Causal Component Analysis
Liang Wendong, Armin Kekić, Julius von Kügelgen +4
Independent Component Analysis (ICA) aims to recover independent latent variables from observed mixtures thereof. Causal Representation Learning (CRL) aims instead to infer causall…