| Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications A Decelle, F Krzakala, C Moore, L Zdeborová Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 84 (6 …, 2011 | 926 | 2011 |
| Inference and phase transitions in the detection of modules in sparse networks A Decelle, F Krzakala, C Moore, L Zdeborová Physical Review Letters 107 (6), 065701, 2011 | 420 | 2011 |
| Creating artificial human genomes using generative neural networks B Yelmen, A Decelle, L Ongaro, D Marnetto, C Tallec, F Montinaro, ... PLoS genetics 17 (2), e1009303, 2021 | 103 | 2021 |
| Archimedean lattices in the bound states of wave interacting particles A Eddi, A Decelle, E Fort, Y Couder Europhysics Letters 87 (5), 56002, 2009 | 77 | 2009 |
| Pseudolikelihood decimation algorithm improving the inference of the interaction network in a general class of ising models A Decelle, F Ricci-Tersenghi Physical review letters 112 (7), 070603, 2014 | 75 | 2014 |
| Hierarchical random energy model of a spin glass M Castellana, A Decelle, S Franz, M Mézard, G Parisi Physical review letters 104 (12), 127206, 2010 | 56 | 2010 |
| Restricted Boltzmann machine: Recent advances and mean-field theory A Decelle, C Furtlehner Chinese Physics B 30 (4), 040202, 2021 | 55 | 2021 |
| Thermodynamics of restricted Boltzmann machines and related learning dynamics A Decelle, G Fissore, C Furtlehner Journal of Statistical Physics 172, 1576-1608, 2018 | 51 | 2018 |
| Spectral dynamics of learning in restricted Boltzmann machines A Decelle, G Fissore, C Furtlehner Europhysics Letters 119 (6), 60001, 2017 | 48 | 2017 |
| T-ReX: a graph-based filament detection method T Bonnaire, N Aghanim, A Decelle, M Douspis Astronomy & Astrophysics 637, A18, 2020 | 41 | 2020 |
| Equilibrium and non-equilibrium regimes in the learning of restricted Boltzmann machines A Decelle, C Furtlehner, B Seoane Advances in Neural Information Processing Systems 34, 5345-5359, 2021 | 38 | 2021 |
| Message passing for optimization and control of a power grid: Model of a distribution system with redundancy L Zdeborová, A Decelle, M Chertkov Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 80 (4 …, 2009 | 26 | 2009 |
| Solving the inverse Ising problem by mean-field methods in a clustered phase space with many states A Decelle, F Ricci-Tersenghi Physical Review E 94 (1), 012112, 2016 | 23 | 2016 |
| Cosmology with cosmic web environments-I. Real-space power spectra T Bonnaire, N Aghanim, J Kuruvilla, A Decelle Astronomy & Astrophysics 661, A146, 2022 | 22 | 2022 |
| Learning a restricted Boltzmann machine using biased Monte Carlo sampling N Béreux, A Decelle, C Furtlehner, B Seoane SciPost Physics 14 (3), 032, 2023 | 18 | 2023 |
| Learning a local symmetry with neural networks A Decelle, V Martin-Mayor, B Seoane Physical Review E 100 (5), 050102, 2019 | 18 | 2019 |
| Detection of cheating by decimation algorithm S Yamanaka, M Ohzeki, A Decelle Journal of the Physical Society of Japan 84 (2), 024801, 2015 | 17 | 2015 |
| Inference of the sparse kinetic Ising model using the decimation method A Decelle, P Zhang Physical Review E 91 (5), 052136, 2015 | 16 | 2015 |
| Extreme value statistics distributions in spin glasses M Castellana, A Decelle, E Zarinelli Physical review letters 107 (27), 275701, 2011 | 14 | 2011 |
| Inverse problems for structured datasets using parallel TAP equations and restricted Boltzmann machines A Decelle, S Hwang, J Rocchi, D Tantari Scientific Reports 11 (1), 19990, 2021 | 13 | 2021 |
Cyril FurtlehnerInriaVerified email at inria.fr
