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Marylou Gabrié
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2020 – today
- 2024
- [c10]Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus:
Stochastic Localization via Iterative Posterior Sampling. ICML 2024 - [i15]Louis Grenioux, Maxence Noble, Marylou Gabrié, Alain Oliviero Durmus:
Stochastic Localization via Iterative Posterior Sampling. CoRR abs/2402.10758 (2024) - 2023
- [j1]Kaze W. K. Wong, Marylou Gabrié, Daniel Foreman-Mackey:
flowMC: Normalizing flow enhanced sampling package for probabilistic inference in JAX. J. Open Source Softw. 8(83): 5021 (2023) - [c9]Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié:
On Sampling with Approximate Transport Maps. ICML 2023: 11698-11733 - [i14]Louis Grenioux, Alain Durmus, Éric Moulines, Marylou Gabrié:
On Sampling with Approximate Transport Maps. CoRR abs/2302.04763 (2023) - [i13]Louis Grenioux, Éric Moulines, Marylou Gabrié:
Balanced Training of Energy-Based Models with Adaptive Flow Sampling. CoRR abs/2306.00684 (2023) - 2022
- [c8]James A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman:
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals. AISTATS 2022: 5949-5986 - [c7]Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines:
Local-Global MCMC kernels: the best of both worlds. NeurIPS 2022 - 2021
- [c6]Hannah Lawrence, David Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié:
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. MSML 2021: 516-567 - [c5]Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli:
On the interplay between data structure and loss function in classification problems. NeurIPS 2021: 8506-8517 - [i12]Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli:
More data or more parameters? Investigating the effect of data structure on generalization. CoRR abs/2103.05524 (2021) - [i11]Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden:
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR abs/2107.05134 (2021) - [i10]Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden:
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods. CoRR abs/2107.08001 (2021) - 2020
- [i9]Hannah Lawrence, David A. Barmherzig, Henry Li, Michael Eickenberg, Marylou Gabrié:
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging. CoRR abs/2012.07386 (2020)
2010 – 2019
- 2019
- [b1]Marylou Gabrié:
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). Paris Sciences et lettres University, France, 2019 - [c4]Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová:
Blind Calibration for Sparse Regression: A State Evolution Analysis. CAMSAP 2019: 649-653 - [i8]Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová:
Blind calibration for compressed sensing: State evolution and an online algorithm. CoRR abs/1910.00285 (2019) - [i7]Marylou Gabrié:
Mean-field inference methods for neural networks. CoRR abs/1911.00890 (2019) - 2018
- [c3]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. NeurIPS 2018: 1826-1836 - [i6]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. CoRR abs/1805.09785 (2018) - 2017
- [i5]Eric W. Tramel, Marylou Gabrié, Andre Manoel, Francesco Caltagirone, Florent Krzakala:
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. CoRR abs/1702.03260 (2017) - [i4]Marylou Gabrié, Varsha Dani, Guilhem Semerjian, Lenka Zdeborová:
Phase transitions in the $q$-coloring of random hypergraphs. CoRR abs/1707.01983 (2017) - 2016
- [c2]Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala:
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. ITW 2016: 265-269 - [i3]Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala:
Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines. CoRR abs/1606.03956 (2016) - [i2]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:
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR abs/1609.04167 (2016) - 2015
- [c1]Marylou Gabrié, Eric W. Tramel, Florent Krzakala:
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy. NIPS 2015: 640-648 - [i1]Marylou Gabrié, Eric W. Tramel, Florent Krzakala:
Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy. CoRR abs/1506.02914 (2015)
Coauthor Index
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