Christian Etmann

On the Connection Between Adversarial Robustness and Saliency Map Interpretability

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-robust counterparts. We aim to quantify this behaviour by considering the alignment between input image a…