Explaining an Image Classifier with a Generative Model Conditioned by Uncertainty

Abstract

We propose to condition a generative model by a given image classifier uncertainty in order to analyze and explain its behavior. Preliminary experiments on synthetic data and a corrupted version of MNIST dataset illustrate the idea

Publication
Uncertainty Meets Explainability| Workshop and Tutorial@ ECML-PKDD 2023