2 papers
math.PR2026
Large deviation principles for convolutional Bayesian neural networks
Federico Bassetti, Vassili De Palma, Lucia Ladelli
While suitably scaled CNNs with Gaussian initialization are known to converge to Gaussian processes as the number of channels diverges, little is known beyond this Gaussian limit.…
math.PR2025
LDP for the covariance process in fully connected neural networks
Luisa Andreis, Federico Bassetti, Christian Hirsch
In this work, we study large deviation properties of the covariance process in fully connected Gaussian deep neural networks. More precisely, we establish a large deviation princip…