Causal Discovery under Scaled Noise: Identifiability and Robust Estimation
representation learning, information theory, and Bayesian deep learning. He was a postdoctoral researcher in the Computational Biology Group at ETH Zürich, a postdoc fellow at the ETH AI Center, and part of [...] Research Center for Trustworthy Data Science and Security and the Department of Statistics, and a member of the ELLIS society. His research is at the intersection of causality and machine learning, focusing [...] Joseph-von-Fraunhoferstrasse 25, 3. Floor, Room 303 Abstract - Causal discovery aims to learn causal networks, i.e., directed acyclic graphs (DAGs), from observational data. Although the problem is no …