2024
DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning
Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Robert Jenssen
ICASSP 2024accepted
The recent development of self-explainable deep learning approaches has focused on integrating well-defined explainability principles into learning process, with the goal of achieving these principles through optimization. In this work, we propose DIB-X, a self-explainable deep learning approach for…