Macris, Nicolas

11 publications

AISTATS 2025 Sampling in High-Dimensions Using Stochastic Interpolants and Forward-Backward Stochastic Differential Equations Anand Jerry George, Nicolas Macris

ICML 2024 Stochastic Gradient Flow Dynamics of Test Risk and Its Exact Solution for Weak Features Rodrigo Veiga, Anastasia Remizova, Nicolas Macris

NeurIPS 2023 Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors Farzad Pourkamali, Nicolas Macris

NeurIPS 2021 Model, Sample, and Epoch-Wise Descents: Exact Solution of Gradient Flow in the Random Feature Model Antoine Bodin, Nicolas Macris

COLT 2021 Rank-One Matrix Estimation: Analytic Time Evolution of Gradient Descent Dynamics Antoine Bodin, Nicolas Macris

NeurIPS 2020 All-or-Nothing Statistical and Computational Phase Transitions in Sparse Spiked Matrix Estimation Jean Barbier, Nicolas Macris, Cynthia Rush

NeurIPS 2020 Information Theoretic Limits of Learning a Sparse Rule Clément Luneau, Jean Barbier, Nicolas Macris

NeurIPS 2018 Entropy and Mutual Information in Models of Deep Neural Networks Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová

COLT 2018 Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová

NeurIPS 2018 The Committee Machine: Computational to Statistical Gaps in Learning a Two-Layers Neural Network Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová

NeurIPS 2016 Mutual Information for Symmetric Rank-One Matrix Estimation: A Proof of the Replica Formula Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová