Aurélien Decelle

2.0k total citations · 1 hit paper
37 papers, 1.1k citations indexed

About

Aurélien Decelle is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Aurélien Decelle has authored 37 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistical and Nonlinear Physics, 16 papers in Artificial Intelligence and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Aurélien Decelle's work include Generative Adversarial Networks and Image Synthesis (12 papers), Model Reduction and Neural Networks (9 papers) and Neural Networks and Applications (9 papers). Aurélien Decelle is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (12 papers), Model Reduction and Neural Networks (9 papers) and Neural Networks and Applications (9 papers). Aurélien Decelle collaborates with scholars based in France, Spain and Italy. Aurélien Decelle's co-authors include Lenka Zdeborová, Florent Krząkała, Cristopher Moore, Cyril Furtlehner, Federico Ricci‐Tersenghi, Beatriz Seoane, Nabila Aghanim, Antonin Eddi, Y. Couder and Emmanuel Fort and has published in prestigious journals such as Physical Review Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and Physical Review B.

In The Last Decade

Aurélien Decelle

35 papers receiving 984 citations

Hit Papers

Asymptotic analysis of the stochastic block model for mod... 2011 2026 2016 2021 2011 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
    2011 379 citations Aurélien Decelle, Florent Krząkała et al. Physical Review E profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aurélien Decelle France 13 568 327 150 137 128 37 1.1k
Yoshiyuki Kabashima Japan 18 267 0.5× 433 1.3× 158 1.1× 113 0.8× 162 1.3× 110 1.4k
Allan Sly United States 20 552 1.0× 375 1.1× 83 0.6× 63 0.5× 220 1.7× 66 1.4k
Peter G. Doyle United States 14 286 0.5× 175 0.5× 106 0.7× 117 0.9× 136 1.1× 24 1.5k
Emanuele Caglioti Italy 20 565 1.0× 326 1.0× 158 1.1× 37 0.3× 182 1.4× 74 2.1k
Guilhem Semerjian France 17 360 0.6× 307 0.9× 71 0.5× 50 0.4× 324 2.5× 30 1.1k
David P. Feldman United States 11 327 0.6× 219 0.7× 133 0.9× 63 0.5× 92 0.7× 16 870
Dario Benedetto Italy 15 131 0.2× 284 0.9× 100 0.7× 35 0.3× 46 0.4× 46 923
Boris Hasselblatt United States 14 1.1k 1.9× 97 0.3× 93 0.6× 44 0.3× 66 0.5× 44 2.2k
Lev Shchur Russia 15 275 0.5× 95 0.3× 27 0.2× 76 0.6× 385 3.0× 86 808
L. R. da Silva Brazil 24 1.2k 2.1× 83 0.3× 185 1.2× 27 0.2× 415 3.2× 132 2.0k

Countries citing papers authored by Aurélien Decelle

Since Specialization
Citations

This map shows the geographic impact of Aurélien Decelle's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aurélien Decelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélien Decelle more than expected).

Fields of papers citing papers by Aurélien Decelle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aurélien Decelle. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aurélien Decelle. The network helps show where Aurélien Decelle may publish in the future.

Co-authorship network of co-authors of Aurélien Decelle

This figure shows the co-authorship network connecting the top 25 collaborators of Aurélien Decelle. A scholar is included among the top collaborators of Aurélien Decelle based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aurélien Decelle. Aurélien Decelle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Decelle, Aurélien, et al.. (2025). Inferring Higher-Order Couplings with Neural Networks.. PubMed. 135(20). 207301–207301.
2.
Biroli, Giulio, et al.. (2025). Cascade of phase transitions in the training of energy-based models*. Journal of Statistical Mechanics Theory and Experiment. 2025(7). 74004–74004.
3.
Decelle, Aurélien, et al.. (2024). Inferring effective couplings with restricted Boltzmann machines. SciPost Physics. 16(4). 6 indexed citations
4.
Carbone, Alessandra, et al.. (2024). Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(2). 1309–1316. 3 indexed citations
5.
Biroli, Giulio, et al.. (2024). Cascade of phase transitions in the training of energy-based models. arXiv (Cornell University). 55591–55619. 2 indexed citations
6.
Aghanim, Nabila, et al.. (2023). Cosmology with cosmic web environments. Astronomy and Astrophysics. 674. A150–A150. 7 indexed citations
7.
Decelle, Aurélien, et al.. (2023). Unsupervised hierarchical clustering using the learning dynamics of restricted Boltzmann machines. Physical review. E. 108(1). 14110–14110. 10 indexed citations
8.
Decelle, Aurélien, Cyril Furtlehner, & Beatriz Seoane. (2022). Equilibrium and non-equilibrium regimes in the learning of restricted Boltzmann machines*. Journal of Statistical Mechanics Theory and Experiment. 2022(11). 114009–114009. 11 indexed citations
9.
Decelle, Aurélien, et al.. (2021). Regularization of Mixture Models for Robust Principal Graph Learning. HAL (Le Centre pour la Communication Scientifique Directe). 7 indexed citations
10.
Decelle, Aurélien & Cyril Furtlehner. (2021). Exact training of Restricted Boltzmann machines on intrinsically low dimensional data. arXiv (Cornell University). 4 indexed citations
11.
Decelle, Aurélien, et al.. (2021). Inverse problems for structured datasets using parallel TAP equations and restricted Boltzmann machines. Scientific Reports. 11(1). 19990–19990. 9 indexed citations
12.
Decelle, Aurélien, V. Martı́n-Mayor, & Beatriz Seoane. (2019). Learning a local symmetry with neural networks. Physical review. E. 100(5). 50102–50102. 12 indexed citations
13.
Decelle, Aurélien & Federico Ricci‐Tersenghi. (2016). Solving the inverse Ising problem by mean-field methods in a clustered phase space with many states. Physical review. E. 94(1). 12112–12112. 13 indexed citations
14.
Decelle, Aurélien, et al.. (2014). Ensemble renormalization group for the random-field hierarchical model. Physical Review E. 89(3). 32132–32132. 5 indexed citations
15.
Decelle, Aurélien & Federico Ricci‐Tersenghi. (2014). Pseudolikelihood Decimation Algorithm Improving the Inference of the Interaction Network in a General Class of Ising Models. Physical Review Letters. 112(7). 70603–70603. 42 indexed citations
16.
Decelle, Aurélien, Florent Krząkała, Cristopher Moore, & Lenka Zdeborová. (2011). Inference and Phase Transitions in the Detection of Modules in Sparse Networks. Physical Review Letters. 107(6). 65701–65701. 217 indexed citations
17.
Castellana, Michele, et al.. (2011). Extreme Value Statistics Distributions in Spin Glasses. Physical Review Letters. 107(27). 275701–275701. 7 indexed citations
18.
Decelle, Aurélien, Florent Krząkała, Cristopher Moore, & Lenka Zdeborová. (2011). Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications. Physical Review E. 84(6). 66106–66106. 379 indexed citations breakdown →
19.
Castellana, Michele, Aurélien Decelle, Silvio Franz, Marc Mézard, & Giorgio Parisi. (2010). Hierarchical Random Energy Model of a Spin Glass. Physical Review Letters. 104(12). 127206–127206. 30 indexed citations
20.
Zdeborová, Lenka, Aurélien Decelle, & Michael Chertkov. (2009). Message passing for optimization and control of a power grid: Model of a distribution system with redundancy. Physical Review E. 80(4). 46112–46112. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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