Beyond the storage capacity: data driven satisfiability transition. - Pietro Rotondo; Mauro Pastore; Marco Gherardi (CoRR, 2020)

A statistical mechanics framework for Bayesian deep neural networks beyond the infinite-width limit. - R. Pacelli; Sebastiano Ariosto; Mauro Pastore; Francesco Ginelli; Marco Gherardi; Pietro Rotondo (Nat. Mac. Intell., 2023)

Restoring balance: principled under/oversampling of data for optimal classification. - Emanuele Loffredo; Mauro Pastore; Simona Cocco; Rémi Monasson (ICML, 2024)

Random features and polynomial rules. - Fabián Aguirre-López; Silvio Franz; Mauro Pastore (CoRR, 2024)

Feature learning in finite-width Bayesian deep linear networks with multiple outputs and convolutional layers. - Federico Bassetti; Marco Gherardi; Alessandro Ingrosso; Mauro Pastore; Pietro Rotondo (CoRR, 2024)

Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation. - Jean Barbier; Francesco Camilli; Minh-Toan Nguyen; Mauro Pastore; Rudy Skerk (CoRR, 2025)

Statistical mechanics of extensive-width Bayesian neural networks near interpolation. - Jean Barbier; Francesco Camilli; Minh-Toan Nguyen; Mauro Pastore; Rudy Skerk (CoRR, 2025)