Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networks

However they remain commonly considered as less accurate, and their properties in learning are still not fully understood. In this paper we clarify the matter: when it comes to classification 1-Lipschitz neural networks enjoy several advantages over their unconstrained counterpart.