RDF/XML JSON-LD N3/Turtle RDF/JSON

Decelle, Aurelien Fabrice aurelien.decelle@upm.es

MATEMÁTICA APLICADA / Universidad Politécnica de Madrid

Publications

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

  • Bachtis, Dimitrios
  • Biroli, Giulio
  • Decelle, Aurelien
  • Seoane, Beatriz

Journal Of Statistical Mechanics-Theory And Experiment - 1/7/2025

10.1088/1742-5468/adec64 View at source

  • ISSN 17425468

Explaining the effects of non-convergent sampling in the training of energy-based models*

  • Agoritsas, Elisabeth
  • Catania, Giovanni
  • Decelle, Aurelien
  • Seoane, Beatriz

Journal Of Statistical Mechanics-Theory And Experiment (p. 064001-064001) - 1/6/2025

10.1088/1742-5468/adde41 View at source

  • ISSN 17425468

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

  • Carbone, Alessandra
  • Decelle, Aurelien
  • Rosset, Lorenzo
  • Seoane, Beatriz

Ieee Transactions On Pattern Analysis And Machine Intelligence (p. 1309-1316) - 1/2/2025

10.1109/tpami.2024.3495999 View at source

  • ISSN 01628828

Inferring High-Order Couplings with Neural Networks

  • A Decelle
  • AJN Gómez
  • B Seoane

Arxiv Preprint Arxiv: - 1/1/2025

  • iMarina

A theoretical framework for overfitting in energy-based modeling

  • G Catania
  • A Decelle
  • C Furtlehner
  • B Seoane

Arxiv Preprint Arxiv: - 1/1/2025

  • iMarina

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

  • T Bonnaire
  • G Catania
  • A Decelle
  • B Seoane

Arxiv Preprint Arxiv: - 1/1/2025

  • iMarina

Copycat perceptron: Smashing barriers through collective learning

  • Catania, Giovanni
  • Decelle, Aurelien
  • Seoane, Beatriz

Physical Review e - 28/6/2024

10.1103/physreve.109.065313 View at source

  • ISSN 1063651X

Inferring effective couplings with restricted Boltzmann machines

  • Decelle, Aurelien
  • Furtlehner, Cyril
  • Gomez, Alfonso De Jesus Navas
  • Seoane, Beatriz

Scipost Physics - 1/4/2024

10.21468/scipostphys.16.4.095 View at source

  • ISSN 25424653

Predicting large scale cosmological structure evolution with GAN-based autoencoders

  • M Ullmo
  • N Aghnim
  • A Decelle
  • M Aragon-Calvo

Arxiv Preprint Arxiv: - 1/1/2024

  • iMarina

Fast, accurate training and sampling of Restricted Boltzmann Machines

  • N Béreux
  • A Decelle
  • C Furtlehner
  • L Rosset
  • B Seoane

Arxiv Preprint Arxiv: - 1/1/2024

  • iMarina

This researcher has no books.

This researcher has no book chapters.

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

  • Agoritsas, Elisabeth
  • Catania, Giovanni
  • Decelle, Aurelien
  • Seoane, Beatriz

Critical Care Medicine (p. 322-336) - 1/1/2023

  • ISSN 00903493
  • iMarina

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

  • Decelle, Aurelien
  • Furtlehner, Cyril
  • Seoane, Beatriz

Advances In Neural Information Processing Systems - 1/1/2021

  • ISSN 10495258
  • iMarina

Creating artificial human genomes using generative neural networks

  • Yelmen, B
  • Decelle, A
  • Ongaro, L
  • Marnetto, D
  • Tallec, C
  • Montinaro, F
  • Furtlehner, C
  • Pagani, L
  • Jay, F
... View more Collapse

European Journal Of Human Genetics (p. 591-592) - 1/12/2020

  • ISSN 10184813
  • iMarina

This researcher has no working papers.

This researcher has no technical reports.

Disordered Physics for Biology and Artificial Intelligence

  • DECELLE, AURELIEN FABRICE (Autor o Coautor)

Period: 20-07-2022 - 19-07-2023

  • iMarina

Física Estadística de modelos basados en una energía

  • DECELLE, AURELIEN FABRICE (Investigador principal (IP))

Period: From 01-01-2022

Type of funding: National

Amount of funding: 78650,00 Euros.

  • iMarina

This researcher has no supervised thesis.

This researcher has no patents or software licenses.

Last data update: 11/10/25 9:46 AM