Marylou Gabrié

35 papers A* 6A 1B 1Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures. CoRR Luigi Fogliani, Bruno Loureiro, Marylou Gabrié
2025	J	`jnl`	A theoretical perspective on mode collapse in variational inference. Mach. Learn. Sci. Technol. Roman Soletskyi, Marylou Gabrié, Bruno Loureiro
2025	J	`jnl`	Improving the evaluation of samplers on multi-modal targets. CoRR Louis Grenioux, Maxence Noble, Marylou Gabrié
2025	A*	`conf`	Learned Reference-based Diffusion Sampler for multi-modal distributions. ICLR Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus
2025	J	`jnl`	Riemannian Stochastic Interpolants for Amorphous Particle Systems. CoRR Louis Grenioux, Leonardo Galliano, Ludovic Berthier, Giulio Biroli, Marylou Gabrié
2025	J	`jnl`	Sampling metastable systems using collective variables and Jarzynski-Crooks paths. J. Comput. Phys. Christoph Schönle, Marylou Gabrié, Tony Lelièvre, Gabriel Stoltz
2024	J	`jnl`	A theoretical perspective on mode collapse in variational inference. CoRR Roman Soletskyi, Marylou Gabrié, Bruno Loureiro
2024	J	`jnl`	Learned Reference-based Diffusion Sampling for multi-modal distributions. CoRR Maxence Noble, Louis Grenioux, Marylou Gabrié, Alain Oliviero Durmus
2024	A*	`conf`	Stochastic Localization via Iterative Posterior Sampling. ICML Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus
2024	J	`jnl`	Stochastic Localization via Iterative Posterior Sampling. CoRR Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus
2023	J	`jnl`	Balanced Training of Energy-Based Models with Adaptive Flow Sampling. CoRR Louis Grenioux, Éric Moulines, Marylou Gabrié
2023	A*	`conf`	On Sampling with Approximate Transport Maps. ICML Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié
2023	J	`jnl`	On Sampling with Approximate Transport Maps. CoRR Louis Grenioux, Alain Durmus, Éric Moulines, Marylou Gabrié
2023	J	`jnl`	flowMC: Normalizing flow enhanced sampling package for probabilistic inference in JAX. J. Open Source Softw. Kaze W. K. Wong, Marylou Gabrié, Daniel Foreman-Mackey
2022	A	`conf`	Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals. AISTATS James A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman
2022	A*	`conf`	Local-Global MCMC kernels: the best of both worlds. NeurIPS Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines
2021	J	`jnl`	Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden
2021	J	`jnl`	Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods. CoRR Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden
2021	J	`jnl`	More data or more parameters? Investigating the effect of data structure on generalization. CoRR Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli
2021	A*	`conf`	On the interplay between data structure and loss function in classification problems. NeurIPS Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli
2021	—	`conf`	Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. MSML Hannah Lawrence, David Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié
2020	J	`jnl`	Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. CoRR Hannah Lawrence, David A. Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié
2019	—	`conf`	Blind Calibration for Sparse Regression: A State Evolution Analysis. CAMSAP Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Blind calibration for compressed sensing: State evolution and an online algorithm. CoRR Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Mean-field inference methods for neural networks. CoRR Marylou Gabrié
2019	—	`—`	Towards an understanding of neural networks: mean-field incursions. (Éléments de compréhension des réseaux de neurones pour l'apprentissage automatique par méthodes de champ moyen). Marylou Gabrié
2018	A*	`conf`	Entropy and mutual information in models of deep neural networks. NeurIPS Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
2018	J	`jnl`	Entropy and mutual information in models of deep neural networks. CoRR Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
2017	J	`jnl`	A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. CoRR Eric W. Tramel, Marylou Gabrié, Andre Manoel, Francesco Caltagirone, Florent Krzakala
2017	J	`jnl`	Phase transitions in the $q$-coloring of random hypergraphs. CoRR Marylou Gabrié, Varsha Dani, Guilhem Semerjian, Lenka Zdeborová
2016	J	`jnl`	Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines. CoRR Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala
2016	B	`conf`	Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. ITW Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala
2016	J	`jnl`	Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR Vinayak Abrol, Olivier Absil, Pierre-Antoine Absil, Sandrine Anthoine, Philippe Antoine, Thomas Arildsen, Nancy Bertin, Folkert Bleichrodt, Jérôme Bobin, Anne Bol, Antoine Bonnefoy, Francesco Caltagirone, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang
2015	—	`conf`	Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy. NIPS Marylou Gabrié, Eric W. Tramel, Florent Krzakala
2015	J	`jnl`	Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy. CoRR Marylou Gabrié, Eric W. Tramel, Florent Krzakala