Aurélien Decelle

Orcid: 0000-0002-3017-0858

Affiliations:
  • Complutense University of Madrid, Spain
  • University of Paris-Saclay, Paris, France


According to our database1, Aurélien Decelle authored at least 27 papers between 2011 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Fast, accurate training and sampling of Restricted Boltzmann Machines.
CoRR, 2024

Cascade of phase transitions in the training of Energy-based models.
CoRR, 2024

Predicting large scale cosmological structure evolution with GAN-based autoencoders.
CoRR, 2024

2023
Deep convolutional and conditional neural networks for large-scale genomic data generation.
PLoS Comput. Biol., October, 2023

Inferring effective couplings with Restricted Boltzmann Machines.
CoRR, 2023

The Copycat Perceptron: Smashing Barriers Through Collective Learning.
CoRR, 2023

Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics.
CoRR, 2023

Unsupervised hierarchical clustering using the learning dynamics of RBMs.
CoRR, 2023

Explaining the effects of non-convergent sampling in the training of Energy-Based Models.
CoRR, 2023

Explaining the effects of non-convergent MCMC in the training of Energy-Based Models.
Proceedings of the International Conference on Machine Learning, 2023

2022
Regularization of Mixture Models for Robust Principal Graph Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Thermodynamics of bidirectional associative memories.
CoRR, 2022

Learning a Restricted Boltzmann Machine using biased Monte Carlo sampling.
CoRR, 2022

The mighty force: statistical inference and high-dimensional statistics.
CoRR, 2022

2021
Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines.
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.
CoRR, 2020

Encoding large scale cosmological structure with Generative Adversarial Networks.
CoRR, 2020

Cascade of Phase Transitions for Multi-Scale Clustering.
CoRR, 2020

Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines.
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.
CoRR, 2019

Learning a Gauge Symmetry with Neural Networks.
CoRR, 2019

2018
Thermodynamics of Restricted Boltzmann Machines and related learning dynamics.
CoRR, 2018

2017
Spectral Learning of Restricted Boltzmann Machines.
CoRR, 2017

2014
Detection of cheating by decimation algorithm.
CoRR, 2014

Computational Complexity, Phase Transitions, and Message-Passing for Community Detection.
CoRR, 2014

2011
Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
CoRR, 2011

Phase transition in the detection of modules in sparse networks
CoRR, 2011


  Loading...