Understanding the effect of sparsity on neural networks robustness

Lukas Timpl, Rahim Entezari, Hanie Sedghi +2

This paper examines the impact of static sparsity on the robustness of a trained network to weight perturbations, data corruption, and adversarial examples. We show that, up to a c…