Aurélien Decelle

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Monte Carlo Sampling

Restricted Boltzmann Machine

Collective Learning

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle, Beatriz Seoane
Cascade of phase transitions in the training of Energy-based models. CoRR (2024)
Marion Ullmo, Nabila Aghanim, Aurélien Decelle, Miguel Aragon-Calvo
Predicting large scale cosmological structure evolution with GAN-based autoencoders. CoRR (2024)
Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane
Fast, accurate training and sampling of Restricted Boltzmann Machines. CoRR (2024)
Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane
Explaining the effects of non-convergent MCMC in the training of Energy-Based Models. ICML (2023)
Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane
Unsupervised hierarchical clustering using the learning dynamics of RBMs. CoRR (2023)
Alessandra Carbone, Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane
Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics. CoRR (2023)
Burak Yelmen, Aurélien Decelle, Leila Lea Boulos, Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Flora Jay
Deep convolutional and conditional neural networks for large-scale genomic data generation. PLoS Comput. Biol. 19 (10) (2023)
Aurélien Decelle, Cyril Furtlehner, Alfonso De Jesus Navas Gómez, Beatriz Seoane
Inferring effective couplings with Restricted Boltzmann Machines. CoRR (2023)
Giovanni Catania, Aurélien Decelle, Beatriz Seoane
The Copycat Perceptron: Smashing Barriers Through Collective Learning. CoRR (2023)
Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane
Explaining the effects of non-convergent sampling in the training of Energy-Based Models. CoRR (2023)
Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane
Learning a Restricted Boltzmann Machine using biased Monte Carlo sampling. CoRR (2022)
Erik Aurell, Jean Barbier, Aurélien Decelle, Roberto Mulet
The mighty force: statistical inference and high-dimensional statistics. CoRR (2022)
Adriano Barra, Giovanni Catania, Aurélien Decelle, Beatriz Seoane
Thermodynamics of bidirectional associative memories. CoRR (2022)
Tony Bonnaire, Aurélien Decelle, Nabila Aghanim
Regularization of Mixture Models for Robust Principal Graph Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines. CoRR (2021)
Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines. NeurIPS (2021)
Tony Bonnaire, Aurélien Decelle, Nabila Aghanim
Regularization of Mixture Models for Robust Principal Graph Learning. CoRR (2021)
Marion Ullmo, Aurélien Decelle, Nabila Aghanim
Encoding large scale cosmological structure with Generative Adversarial Networks. CoRR (2020)
Aurélien Decelle, Cyril Furtlehner
Restricted Boltzmann Machine, recent advances and mean-field theory. CoRR (2020)
Giancarlo Fissore, Yufei Han, Aurélien Decelle, Cyril Furtlehner
Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines. STAIRS@ECAI (2020)
Tony Bonnaire, Aurélien Decelle, Nabila Aghanim
Cascade of Phase Transitions for Multi-Scale Clustering. CoRR (2020)
Aurélien Decelle, Victor Martin-Mayor, Beatriz Seoane
Learning a Gauge Symmetry with Neural Networks. CoRR (2019)
Giancarlo Fissore, Aurélien Decelle, Cyril Furtlehner, Yufei Han
Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines. CoRR (2019)
Aurélien Decelle, Cyril Furtlehner
Gaussian-Spherical Restricted Boltzmann Machines. CoRR (2019)
Aurélien Decelle, Giancarlo Fissore, Cyril Furtlehner
Thermodynamics of Restricted Boltzmann Machines and related learning dynamics. CoRR (2018)