Causal Discovery under Scaled Noise: Identifiability and Robust Estimation
the intersection of causality and machine learning, focusing on causal discovery, causal representation learning, information theory, and Bayesian deep learning. He was a postdoctoral researcher in the [...] 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 [...] Zürich, a postdoc fellow at the ETH AI Center, and part of the Medical Data Science Group. He did his PhD in the Exploratory Data Analysis group affiliated with the CISPA Helmholtz Center for Information Security …
