Bayes-optimal limits in structured PCA, and how to reach them. - Jean Barbier; Francesco Camilli; Marco Mondelli; Manuel Sáenz (CoRR, 2022)

Matrix factorization with neural networks. - Francesco Camilli; Marc Mézard (CoRR, 2022)

Central limit theorem for the overlaps on the Nishimori line. - Francesco Camilli; Pierluigi Contucci; Emanuele Mingione (CoRR, 2023)

Fundamental limits of overparametrized shallow neural networks for supervised learning. - Francesco Camilli; Daria Tieplova; Jean Barbier (CoRR, 2023)

The Decimation Scheme for Symmetric Matrix Factorization. - Francesco Camilli; Marc Mézard (CoRR, 2023)

Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise. - Jean Barbier; Francesco Camilli; Marco Mondelli; Yizhou Xu (CoRR, 2024)

On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance. - Jean Barbier; Francesco Camilli; Justin Ko; Koki Okajima (CoRR, 2024)

The Onset of Parisi's Complexity in a Mismatched Inference Problem. - Francesco Camilli; Pierluigi Contucci; Emanuele Mingione (Entropy, 2024)

Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime. - Francesco Camilli; Daria Tieplova; Eleonora Bergamin; Jean Barbier (COLT, 2025)

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)