A Practical Guide to Statistical Distances for Evaluating Generative Models in Science

1 code implementation • 19 Mar 2024 • Sebastian Bischoff, Alana Darcher, Michael Deistler, Richard Gao, Franziska Gerken, Manuel Gloeckler, Lisa Haxel, Jaivardhan Kapoor, Janne K Lappalainen, Jakob H Macke, Guy Moss, Matthijs Pals, Felix Pei, Rachel Rapp, A Erdem Sağtekin, Cornelius Schröder, Auguste Schulz, Zinovia Stefanidi, Shoji Toyota, Linda Ulmer, Julius Vetter

To demonstrate how these distances are used in practice, we evaluate generative models from different scientific domains, namely a model of decision making and a model generating medical images.

Decision Making

Out-of-Distribution Optimality of Invariant Risk Minimization

no code implementations • 22 Jul 2023 • Shoji Toyota, Kenji Fukumizu

risk.

Invariance Learning based on Label Hierarchy

no code implementations • 29 Mar 2022 • Shoji Toyota, Kenji Fukumizu

Invariance Learning (IL) has been developed recently to overcome this shortcoming; using training data in many domains, IL estimates such a predictor that is invariant to a change of domain.