Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles. - Carlo Baldassi; Christian Borgs; Jennifer T. Chayes; Alessandro Ingrosso; Carlo Lucibello; Luca Saglietti; Riccardo Zecchina (CoRR, 2016)

Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes. - Carlo Baldassi; Christian Borgs; Jennifer T. Chayes; Alessandro Ingrosso; Carlo Lucibello; Luca Saglietti; Riccardo Zecchina (Proc. Natl. Acad. Sci. USA, 2016)

On the role of synaptic stochasticity in training low-precision neural networks. - Carlo Baldassi; Federica Gerace; Hilbert J. Kappen; Carlo Lucibello; Luca Saglietti; Enzo Tartaglione; Riccardo Zecchina (CoRR, 2017)

Gaussian Process Prior Variational Autoencoders. - Francesco Paolo Casale; Adrian V. Dalca; Luca Saglietti; Jennifer Listgarten; Nicoló Fusi (NeurIPS, 2018)

Out of equilibrium Statistical Physics of learning. - Luca Saglietti (2018)

Generalized Approximate Survey Propagation for High-Dimensional Estimation. - Carlo Lucibello; Luca Saglietti; Yue M. Lu (ICML, 2019)

Solvable Model for Inheriting the Regularization through Knowledge Distillation. - Luca Saglietti; Lenka Zdeborová (MSML, 2021)

Large deviations in the perceptron model and consequences for active learning. - Hugo Cui; Luca Saglietti; Lenka Zdeborová (Mach. Learn. Sci. Technol., 2021)

An Analytical Theory of Curriculum Learning in Teacher-Student Networks. - Luca Saglietti; Stefano Sarao Mannelli; Andrew M. Saxe (NeurIPS, 2022)

Inducing bias is simpler than you think. - Stefano Sarao Mannelli; Federica Gerace; Negar Rostamzadeh; Luca Saglietti (CoRR, 2022)

Probing transfer learning with a model of synthetic correlated datasets. - Federica Gerace; Luca Saglietti; Stefano Sarao Mannelli; Andrew M. Saxe; Lenka Zdeborová (Mach. Learn. Sci. Technol., 2022)

Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (ITW, 2023)

Optimal transfer protocol by incremental layer defrosting. - Federica Gerace; Diego Doimo; Stefano Sarao Mannelli; Luca Saglietti; Alessandro Laio (CoRR, 2023)

Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (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)

Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks. - Stefano Sarao Mannelli; Yaraslau Ivashinka; Andrew M. Saxe; Luca Saglietti (ICML, 2024)

The twin peaks of learning neural networks. - Elizaveta Demyanenko; Christoph Feinauer; Enrico M. Malatesta; Luca Saglietti (CoRR, 2024)

The phase diagram of compressed sensing with ℓ0-norm regularization. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (CoRR, 2024)

How transformers learn structured data: insights from hierarchical filtering. - Jerome Garnier-Brun; Marc Mézard; Emanuele Moscato; Luca Saglietti (CoRR, 2024)

How to choose the right transfer learning protocol? A qualitative analysis in a controlled set-up. - Federica Gerace; Diego Doimo; Stefano Sarao Mannelli; Luca Saglietti; Alessandro Laio (Trans. Mach. Learn. Res., 2024)

On the Bias of Next-Token Predictors Toward Systematically Inefficient Reasoning: A Shortest-Path Case Study. - Riccardo Alberghi; Elizaveta Demyanenko; Luca Biggio; Luca Saglietti (CoRR, 2025)