An improved Belief Propagation algorithm finds many Bethe states in the random field Ising model on random graphs. - Gabriele Perugini; Federico Ricci-Tersenghi (CoRR, 2017)

Entropic gradient descent algorithms and wide flat minima. - Fabrizio Pittorino; Carlo Lucibello; Christoph Feinauer; Enrico M. Malatesta; Gabriele Perugini; Carlo Baldassi; Matteo Negri; Elizaveta Demyanenko; Riccardo Zecchina (CoRR, 2020)

Entropic gradient descent algorithms and wide flat minima. - Fabrizio Pittorino; Carlo Lucibello; Christoph Feinauer; Gabriele Perugini; Carlo Baldassi; Elizaveta Demyanenko; Riccardo Zecchina (ICLR, 2021)

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)

Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry. - Fabrizio Pittorino; Antonio Ferraro; Gabriele Perugini; Christoph Feinauer; Carlo Baldassi; Riccardo Zecchina (ICML, 2022)

Deep learning via message passing algorithms based on belief propagation. - Carlo Lucibello; Fabrizio Pittorino; Gabriele Perugini; Riccardo Zecchina (Mach. Learn. Sci. Technol., 2022)

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

Typical and atypical solutions in non-convex neural networks with discrete and continuous weights. - Carlo Baldassi; Enrico M. Malatesta; Gabriele Perugini; Riccardo Zecchina (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)

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)