A new framework for evaluating model out-of-distribution generalisation for the biochemical domain
Published in The Thirteenth International Conference on Learning Representations, 2025
Abstract
This paper discusses a new framework for evaluating model performance in new data. It offers metrics for choosing the best similarity function for a given biochemical prediction task and for estimating model performance conditioned on a deployment distribution.