149 citations · 545 across the 20 of their papers we have counts for
3 papers · 1 filter
Density of states in neural networks: an in-depth exploration of learning in parameter space
Margherita Mele, Roberto Menichetti, Alessandro Ingrosso +1
Learning in neural networks critically hinges on the intricate geometry of the loss landscape associated with a given task. Traditionally, most research has focused on finding spec…
Statistical mechanics of transfer learning in fully-connected networks in the proportional limit
Alessandro Ingrosso, Rosalba Pacelli, Pietro Rotondo +1
Transfer learning (TL) is a well-established machine learning technique to boost the generalization performance on a specific (target) task using information gained from a related…
Feature learning in finite-width Bayesian deep linear networks with multiple outputs and convolutional layers
Federico Bassetti, Marco Gherardi, Alessandro Ingrosso +2
Deep linear networks have been extensively studied, as they provide simplified models of deep learning. However, little is known in the case of finite-width architectures with mult…