Prototypical Self-Explainable Models Without Re-training

no code implementations • 13 Dec 2023 • Srishti Gautam, Ahcene Boubekki, Marina M. C. Höhne, Michael C. Kampffmeyer

Explainable AI (XAI) has unfolded in two distinct research directions with, on the one hand, post-hoc methods that explain the predictions of a pre-trained black-box model and, on the other hand, self-explainable models (SEMs) which are trained directly to provide explanations alongside their predictions.

Decision Making Explainable Models

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model

1 code implementation • 15 Oct 2022 • Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina MC Höhne, Michael Kampffmeyer

The need for interpretable models has fostered the development of self-explainable classifiers.