Gabrie, Marylou

12 publications

ICLRW 2025 Improving the Evaluation of Samplers on Multi-Modal Targets Louis Grenioux, Maxence Noble, Marylou Gabrié

ICLR 2025 Learned Reference-Based Diffusion Sampler for Multi-Modal Distributions Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus

ICML 2024 Stochastic Localization via Iterative Posterior Sampling Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus

ICMLW 2023 Balanced Training of Energy-Based Models with Adaptive Flow Sampling Louis Grenioux, Eric Moulines, Marylou Gabrié

ICML 2023 On Sampling with Approximate Transport Maps Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié

NeurIPSW 2023 Optimizing Markov Chain Monte Carlo Convergence with Normalizing Flows and Gibbs Sampling Christoph Schönle, Marylou Gabrié

AISTATS 2022 Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals James Brofos, Marylou Gabrie, Marcus A. Brubaker, Roy R. Lederman

NeurIPS 2022 Local-Global MCMC Kernels: The Best of Both Worlds Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines

ICMLW 2021 Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden

NeurIPS 2021 On the Interplay Between Data Structure and Loss Function in Classification Problems Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli

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

NeurIPS 2015 Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer Free Energy Marylou Gabrie, Eric W Tramel, Florent Krzakala