Andrea Gimelli

Leveraging Over-Parameterization to Improve the Verifiability of Neural Networks

Over-parameterized neural networks, i.e., models with excess capacity that can fit training data exactly, have demonstrated superior generalization performance compared to classical models with balanced capacity. Nevertheless, their deployment in safety-critical domains re- mains severely constraine