Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (CoRR, 2018)

Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. - Stefano Sarao Mannelli; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (ICML, 2019)

Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2019)

Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model. - Stefano Sarao Mannelli; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (CoRR, 2019)

Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (NeurIPS, 2020)

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. - Stefano Sarao Mannelli; Eric Vanden-Eijnden; Lenka Zdeborová (NeurIPS, 2020)

Thresholds of descending algorithms in inference problems. - Stefano Sarao Mannelli; Lenka Zdeborová (CoRR, 2020)

Winning the competition: enhancing counter-contagion in SIS-like epidemic processes. - Argyris Kalogeratos; Stefano Sarao Mannelli (CoRR, 2020)

Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver. - Levent Sagun; Çaglar Gülçehre; Adriana Romero; Negar Rostamzadeh; Stefano Sarao Mannelli (CoRR, 2020)

Epidemic mitigation by statistical inference from contact tracing data. - Antoine Baker; Indaco Biazzo; Alfredo Braunstein; Giovanni Catania; Luca Dall'Asta; Alessandro Ingrosso; Florent Krzakala; Fabio Mazza; Marc Mézard; Anna Paola Muntoni; Maria Refinetti; Stefano Sarao Mannelli; et al. (CoRR, 2020)

Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems. - Stefano Sarao Mannelli; Pierfrancesco Urbani (NeurIPS, 2021)

Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problem. - Stefano Sarao Mannelli; Pierfrancesco Urbani (CoRR, 2021)

Maslow's Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation. - Sebastian Lee; Stefano Sarao Mannelli; Claudia Clopath; Sebastian Goldt; Andrew M. Saxe (ICML, 2022)

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)

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

The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions. - Nishil Patel; Sebastian Lee; Stefano Sarao Mannelli; Sebastian Goldt; Andrew M. Saxe (CoRR, 2023)

Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning. - Jin Hwa Lee; Stefano Sarao Mannelli; Andrew M. Saxe (ICML, 2024)

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)

Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. - Anchit Jain; Rozhin Nobahari; Aristide Baratin; Stefano Sarao Mannelli (NeurIPS, 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)

A Theory of Initialisation's Impact on Specialisation. - Devon Jarvis; Sebastian Lee; Clémentine Carla Juliette Dominé; Andrew M. Saxe; Stefano Sarao Mannelli (ICLR, 2025)

Optimal Protocols for Continual Learning via Statistical Physics and Control Theory. - Francesco Mori; Stefano Sarao Mannelli; Francesca Mignacco (ICLR, 2025)