Unveiling the structure of wide flat minima in neural networks. - Carlo Baldassi; Clarissa Lauditi; Enrico M. Malatesta; Gabriele Perugini; Riccardo Zecchina (CoRR, 2021)

Learning through atypical "phase transitions" in overparameterized neural networks. - Carlo Baldassi; Clarissa Lauditi; Enrico M. Malatesta; Rosalba Pacelli; Gabriele Perugini; Riccardo Zecchina (CoRR, 2021)

The Hidden-Manifold Hopfield Model and a learning phase transition. - Matteo Negri; Clarissa Lauditi; Gabriele Perugini; Carlo Lucibello; Enrico M. Malatesta (CoRR, 2023)

The star-shaped space of solutions of the spherical negative perceptron. - Brandon Livio Annesi; Clarissa Lauditi; Carlo Lucibello; Enrico M. Malatesta; Gabriele Perugini; Fabrizio Pittorino; Luca Saglietti (CoRR, 2023)

Sparse Representations, Inference and Learning. - Clarissa Lauditi; Emanuele Troiani; Marc Mézard (CoRR, 2023)

Random Features Hopfield Networks generalize retrieval to previously unseen examples. - Silvio Kalaj; Clarissa Lauditi; Gabriele Perugini; Carlo Lucibello; Enrico M. Malatesta; Matteo Negri (CoRR, 2024)

Adaptive kernel predictors from feature-learning infinite limits of neural networks. - Clarissa Lauditi; Blake Bordelon; Cengiz Pehlevan (CoRR, 2025)

Generalization performance of narrow one-hidden layer networks in the teacher-student setting. - Jean Barbier; Federica Gerace; Alessandro Ingrosso; Clarissa Lauditi; Enrico M. Malatesta; Gibbs Nwemadji; Rodrigo Pérez Ortiz (CoRR, 2025)

Transfer Learning in Infinite Width Feature Learning Networks. - Clarissa Lauditi; Blake Bordelon; Cengiz Pehlevan (CoRR, 2025)