Marylou Gabrié
Marylou Gabrié
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Entropy and mutual information in models of deep neural networks
M Gabrié, A Manoel, C Luneau, J Barbier, N Macris, F Krzakala, ...
Advances in Neural Information Processing Systems 2018 (31), 1821--183, 2019
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy
M Gabrié, EW Tramel, F Krzakala
Advances in Neural Information Processing Systems, 640-648, 2015
Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines
EW Tramel, M Gabrié, A Manoel, F Caltagirone, F Krzakala
Physical Review X 8 (4), 041006, 2018
Mean-field inference methods for neural networks
M Gabrié
Journal of Physics A: Mathematical and Theoretical 53 (22), 223002, 2020
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines
EW Tramel, A Manoel, F Caltagirone, M Gabrié, F Krzakala
2016 IEEE Information Theory Workshop (ITW), 265-269, 2016
Phase transitions in the q-coloring of random hypergraphs
M Gabrié, V Dani, G Semerjian, L Zdeborová
Journal of Physics A: Mathematical and Theoretical 50 (50), 505002, 2017
Adaptive Monte Carlo augmented with normalizing flows
M Gabrié, GM Rotskoff, E Vanden-Eijnden
Proceedings of the National Academy of Sciences 119 (10), e2109420119, 2022
Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imaging
H Lawrence, DA Barmherzig, H Li, M Eickenberg, M Gabrié
arXiv preprint arXiv:2012.07386, 2020
On the interplay between data structure and loss function in classification problems
S d'Ascoli, M Gabrié, L Sagun, G Biroli
arXiv preprint arXiv:2103.05524, 2021
Towards an understanding of neural networks: mean-field incursions
M Gabrié
Paris Sciences et Lettres (ComUE), 2019
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods
M Gabrié, GM Rotskoff, E Vanden-Eijnden
ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals
J Brofos, M Gabrié, MA Brubaker, RR Lederman
International Conference on Artificial Intelligence and Statistics, 5949-5986, 2022
Blind calibration for compressed sensing: State evolution and an online algorithm
M Gabrié, J Barbier, F Krzakala, L Zdeborová
Journal of Physics A: Mathematical and Theoretical 53 (33), 334004, 2020
Modern applications of machine learning in quantum sciences
A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ...
arXiv preprint arXiv:2204.04198, 2022
Low-Photon Holographic Phase Retrieval via a Deep Decoder Neural Network
H Lawrence, DA Barmherzig, M Eickenberg, M Gabrie
Optical Sensors, JTu5A. 19, 2021
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks
C Domingo-Enrich, A Bietti, M Gabrié, J Bruna, E Vanden-Eijnden
arXiv preprint arXiv:2107.05134, 2021
Blind Calibration for Sparse Regression: A State Evolution Analysis
M Gabrié, J Barbier, F Krzakala, L Zdeborová
2019 IEEE 8th International Workshop on Computational Advances in Multi …, 2019
Proceedings of the third" international Traveling Workshop on Interactions between Sparse models and Technology"(iTWIST'16)
V Abrol, O Absil, PA Absil, S Anthoine, P Antoine, T Arildsen, N Bertin, ...
arXiv preprint arXiv:1609.04167, 2016
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