Adrian Rodriguez-Munoz*

Characterizing Model Robustness via Natural Input Gradients

"Adversarially robust models are locally smooth around each data sample so that small perturbations cannot drastically change model outputs. In modern systems, such smoothness is usually obtained via Adversarial Training, which explicitly enforces models to perform well on perturbed examples. In thi…