On the Connection Between Adversarial Robustness and Saliency Map Interpretability

Christian Etmann, Sebastian Lunz, Peter Maass, Carola Schönlieb

Abstract: Recent studies on the adversarial vulnerability of neural networks have shown that models trained to be more robust to adversarial attacks exhibit more interpretable saliency maps than their non-ro...