Our guest speaker is Professor Jonas Peters from the department of mathematical sciences at the University of Copenhagen and you are all cordially invited to the CVG Seminar on May 27th at 2:30 p.m. CET on Zoom (passcode is 486210), where‪ Jonas will give a talk titled “Causality and Distribution Generalization“.

Abstract

Purely predictive methods do not perform well when the test distribution changes too much from the training distribution. Causal models are known to be stable with respect to distributional shifts such as arbitrarily strong interventions on the covariates but do not perform well when the test distribution differs only mildly from the training distribution. We discuss methods such as Anchor Regression, Stabilized Regression, and CausalKinetiX that trade-off between causal and predictive models to obtain favorable generalization properties. We discuss possible extensions to nonlinear models and the theoretical limitations of such methodology.

Bio

Jonas is a professor in statistics at the Department of Mathematical Sciences at the University of Copenhagen. Previously, he has been a group leader at the Max-Planck-Institute for Intelligent Systems in Tuebingen and a Marie Curie fellow at the Seminar for Statistics, ETH Zurich. He studied Mathematics at the University of Heidelberg and the University of Cambridge and obtained his Ph.D. jointly from MPI and ETH. He is interested in inferring causal relationships from different types of data and in building statistical methods that are robust with respect to distributional shifts. In his research, Jonas seeks to combine theory, methodology, and applications. His work relates to areas such as computational statistics, causal inference, graphical models, independence testing, or high-dimensional statistics.