Aurélien Decelle

According to our database, Aurélien Decelle authored at least 31 papers between 2011 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

On the role of non-linear latent features in bipartite generative neural networks.

Tony Bonnaire, Giovanni Catania, Aurélien Decelle, Beatriz Seoane

CoRR, June, 2025

Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics.

Alessandra Carbone, Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane

IEEE Trans. Pattern Anal. Mach. Intell., February, 2025

A theoretical framework for overfitting in energy-based modeling.

Giovanni Catania, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane

CoRR, January, 2025

Inferring High-Order Couplings with Neural Networks.

Aurélien Decelle, Alfonso De Jesus Navas Gómez, Beatriz Seoane

CoRR, January, 2025

Fast training and sampling of Restricted Boltzmann Machines.

Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Fast, accurate training and sampling of Restricted Boltzmann Machines.

Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane

CoRR, 2024

Predicting large scale cosmological structure evolution with GAN-based autoencoders.

Marion Ullmo, Nabila Aghanim, Aurélien Decelle, Miguel Aragon-Calvo

CoRR, 2024

Cascade of phase transitions in the training of energy-based models.

Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle, Beatriz Seoane

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Deep convolutional and conditional neural networks for large-scale genomic data generation.

Burak Yelmen, Aurélien Decelle, Leila Lea Boulos, Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Flora Jay

PLoS Comput. Biol., October, 2023

Inferring effective couplings with Restricted Boltzmann Machines.

Aurélien Decelle, Cyril Furtlehner, Alfonso De Jesus Navas Gómez, Beatriz Seoane

CoRR, 2023

The Copycat Perceptron: Smashing Barriers Through Collective Learning.

Giovanni Catania, Aurélien Decelle, Beatriz Seoane

CoRR, 2023

Unsupervised hierarchical clustering using the learning dynamics of RBMs.

Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane

CoRR, 2023

Explaining the effects of non-convergent sampling in the training of Energy-Based Models.

Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane

CoRR, 2023

Explaining the effects of non-convergent MCMC in the training of Energy-Based Models.

Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane

Proceedings of the International Conference on Machine Learning, 2023

2022

Regularization of Mixture Models for Robust Principal Graph Learning.

Tony Bonnaire, Aurélien Decelle, Nabila Aghanim

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Thermodynamics of bidirectional associative memories.

Adriano Barra, Giovanni Catania, Aurélien Decelle, Beatriz Seoane

CoRR, 2022

Learning a Restricted Boltzmann Machine using biased Monte Carlo sampling.

Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane

CoRR, 2022

The mighty force: statistical inference and high-dimensional statistics.

Erik Aurell, Jean Barbier, Aurélien Decelle, Roberto Mulet

CoRR, 2022

2021

Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines.

Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Restricted Boltzmann Machine, recent advances and mean-field theory.

Aurélien Decelle, Cyril Furtlehner

CoRR, 2020

Encoding large scale cosmological structure with Generative Adversarial Networks.

Marion Ullmo, Aurélien Decelle, Nabila Aghanim

CoRR, 2020

Cascade of Phase Transitions for Multi-Scale Clustering.

Tony Bonnaire, Aurélien Decelle, Nabila Aghanim

CoRR, 2020

Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines.

Giancarlo Fissore, Yufei Han, Aurélien Decelle, Cyril Furtlehner

Proceedings of the 9th European Starting AI Researchers' Symposium 2020 co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), 2020

2019

Gaussian-Spherical Restricted Boltzmann Machines.

Aurélien Decelle, Cyril Furtlehner

CoRR, 2019

Learning a Gauge Symmetry with Neural Networks.

Aurélien Decelle, Victor Martin-Mayor, Beatriz Seoane

CoRR, 2019

2018

Thermodynamics of Restricted Boltzmann Machines and related learning dynamics.

Aurélien Decelle, Giancarlo Fissore, Cyril Furtlehner

CoRR, 2018

2017

Spectral Learning of Restricted Boltzmann Machines.

Aurélien Decelle, Giancarlo Fissore, Cyril Furtlehner

CoRR, 2017

2014

Detection of cheating by decimation algorithm.

Shogo Yamanaka, Masayuki Ohzeki, Aurélien Decelle

CoRR, 2014

Computational Complexity, Phase Transitions, and Message-Passing for Community Detection.

Aurélien Decelle, Janina Hüttel, Alaa Saade, Cristopher Moore

CoRR, 2014

2011

Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications

Aurélien Decelle, Florent Krzakala, Cristopher Moore, Lenka Zdeborová

CoRR, 2011

Phase transition in the detection of modules in sparse networks

Aurélien Decelle, Florent Krzakala, Cristopher Moore, Lenka Zdeborová

CoRR, 2011