collaborators

5 papers

math.PR2026

Phase Transitions in the Fluctuations of Functionals of Random Neural Networks

Simmaco Di Lillo, Leonardo Maini, Domenico Marinucci

We establish central and non-central limit theorems for sequences of functionals of the Gaussian output of an infinitely-wide random neural network on the d-dimensional sphere . We…

math.PR2026

Fractal and Regular Geometry of Deep Neural Networks

Simmaco Di Lillo, Domenico Marinucci, Michele Salvi +1

We study the geometric properties of random neural networks by investigating the boundary volumes of their excursion sets for different activation functions, as the depth increases…

math.PR2026

Large deviation principles and functional limit theorems in the deep limit of wide random neural networks

Simmaco Di Lillo, Claudio Macci, Barbara Pacchiarotti

This paper studies large deviation principles and weak convergence, both at the level of finite-dimensional distributions and in functional form, for a class of continuous, isotrop…

stat.ML2025

Critical Points of Random Neural Networks

Simmaco Di Lillo

This work investigates the expected number of critical points of random neural networks with different activation functions as the depth increases in the infinite-width limit. Unde…

stat.ML2025

Spectral complexity of deep neural networks

Simmaco Di Lillo, Domenico Marinucci, Michele Salvi +1

It is well-known that randomly initialized, push-forward, fully-connected neural networks weakly converge to isotropic Gaussian processes, in the limit where the width of all layer…