1 citations · 1 across the 3 of their papers we have counts for
3 papers
Topological obstruction to the training of shallow ReLU neural networks
Marco Nurisso, Pierrick Leroy, Francesco Vaccarino
Studying the interplay between the geometry of the loss landscape and the optimization trajectories of simple neural networks is a fundamental step for understanding their behavior…
Higher-order Laplacian Renormalization
Marco Nurisso, Marta Morandini, Maxime Lucas +3
We propose a cross-order Laplacian renormalization group (X-LRG) scheme for arbitrary higher-order networks. The renormalization group is a pillar of the theory of scaling, scale-i…
A unified framework for Simplicial Kuramoto models
Marco Nurisso, Alexis Arnaudon, Maxime Lucas +4
Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified frame…