Publications

Using HalTools

Publications of the team

Publications of the permanent members on HAL

Publications of the former permanent members (while in TAO/TAU)

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299 documents

Journal articles80 documents

  • Thi-Tuyet-Trang Chau, Anna E. Dudek, Hernando Ombao, Sylvain Chevallier. Impact of Surface Ocean CO2 Atlas (SOCAT) observing network extensions on the quantification of global air-sea CO2 fluxes. Science of the Total Environment, In press, 999, pp.180265. ⟨10.1016/j.scitotenv.2025.180265⟩. ⟨hal-05209651⟩
  • Gianluca Fasano, Cristina Marras, Emilio Sanfilippo, Monica Brinzei, Mathieu Husson, et al.. Unlocking the Potential of DH+AI: Opportunities, Challenges, and Recommendations. La Lettre de l'InSHS, 2025, 4 (92), pp.48-50. ⟨hal-05052377⟩
  • Alessandro Leite, Marc Schoenauer. Memetic Semantic Boosting for Symbolic Regression. Genetic Programming and Evolvable Machines, 2025, 26 (11), pp.11. ⟨10.1007/s10710-024-09506-1⟩. ⟨hal-04911540⟩
  • Thibault de Surrel, Sylvain Chevallier, Fabien Lotte, Florian Yger. Geometry-Aware visualization of high dimensional Symmetric Positive Definite matrices. Transactions on Machine Learning Research Journal, 2025. ⟨hal-04942016v2⟩
  • Emmanuel Menier, Sebastian Kaltenbach, Mouadh Yagoubi, Marc Schoenauer, Petros Koumoutsakos. Interpretable learning of effective dynamics for multiscale systems. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2025, 481 (2306), pp.20240167. ⟨10.1098/rspa.2024.0167⟩. ⟨hal-04392797⟩
  • Pierre Barbault, Matthieu Kowalski, Charles Soussen. LEMUR: Latent EM Unsupervised Regression for Sparse Inverse Problems. IEEE Transactions on Signal Processing, 2025, 73, pp.2087-2098. ⟨10.1109/TSP.2025.3565018⟩. ⟨hal-04542061v2⟩
  • Gerhard Jung, Rinske M Alkemade, Victor Bapst, Daniele Coslovich, Laura Filion, et al.. Roadmap on machine learning glassy liquids. Nature Reviews Physics, 2025, 7 (2), pp.91-104. ⟨10.1038/s42254-024-00791-4⟩. ⟨hal-04344224⟩
  • Edgar Jaber, Vincent Blot, Nicolas Brunel, Vincent Chabridon, Emmauel Remy, et al.. Conformal Approach to Gaussian Process Surrogate Evaluation with Coverage Guarantees. Journal of Machine Learning for Modeling and Computing, 2025, 6 (3), pp.37-68. ⟨10.1615/JMachLearnModelComput.2025054687⟩. ⟨hal-05161190⟩
  • Ilaria Paga, Jian He, Marco Baity-Jesi, Enrico Calore, Andrés Cruz, et al.. Quantifying memory in spin glasses. Physical Review Letters, 2024, 133 (25), pp.256704. ⟨10.1103/PhysRevLett.133.256704⟩. ⟨hal-04344048⟩
  • Matthieu Nastorg, Michele Alessandro Bucci, Thibault Faney, Jean-Marc Gratien, Guillaume Charpiat, et al.. An implicit GNN solver for Poisson-like problems. Computers & Mathematics with Applications, 2024, 176, pp.270-288. ⟨10.1016/j.camwa.2024.10.036⟩. ⟨hal-04919611⟩
  • Vincenzo Maria Schimmenti, Giuseppe Petrillo, Alberto Rosso, François P. Landes. Assessing the Predictive Power of GPS‐Based Ground Deformation Data for Aftershock Forecasting. Seismological Research Letters, 2024, 95 (6), pp.3243-3249. ⟨10.1785/0220240008⟩. ⟨hal-04352596⟩
  • Manon Verbockhaven, Théo Rudkiewicz, Sylvain Chevallier, Guillaume Charpiat. Growing Tiny Networks: Spotting Expressivity Bottlenecks and Fixing Them Optimally. Transactions on Machine Learning Research Journal, 2024. ⟨hal-04591472v2⟩
  • Igor Carrara, Bruno Aristimunha, Marie-Constance Corsi, Raphael Yokoingawa de Camargo, Sylvain Chevallier, et al.. Geometric Neural Network based on Phase Space for BCI decoding. Journal of Neural Engineering, 2024, ⟨10.1088/1741-2552/ad88a2⟩. ⟨hal-04500580⟩
  • Manh Hung Nguyen, Lisheng Sun-Hosoya, Isabelle Guyon. Meta-Learning from Learning Curves for Budget-Limited Algorithm Selection. Pattern Recognition Letters, 2024, 185, pp.225-231. ⟨10.1016/j.patrec.2024.08.010⟩. ⟨hal-04719035⟩
  • Rahul Chacko, François Landes, Giulio Biroli, Olivier Dauchot, Andrea Liu, et al.. Dynamical Facilitation Governs the Equilibration Dynamics of Glasses. Physical Review X, 2024, 14 (3), pp.031012. ⟨10.1103/PhysRevX.14.031012⟩. ⟨hal-04749267⟩
  • Gianfranco Durin, Vincenzo Maria Schimmenti, Marco Baiesi, Arianna Casiraghi, Alessandro Magni, et al.. Earthquake-like dynamics in ultrathin magnetic film. Physical Review B, 2024, 110, pp.L020405. ⟨10.1103/PhysRevB.110.L020405⟩. ⟨hal-04352576⟩
  • Yvenn Amara-Ouali, Yannig Goude, Nathan Doumèche, Pascal Veyret, Alexis Thomas, et al.. Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge. Journal of Data-centric Machine Learning Research, 2024, 1. ⟨hal-04119408⟩
  • Paola Tubaro, Antonio A Casilli. Who bears the burden of a pandemic? COVID-19 and the transfer of risk to digital platform workers. American Behavioral Scientist, 2024, 68 (8), pp.961-982. ⟨10.1177/00027642211066027⟩. ⟨hal-03369291⟩
  • Francesco Saverio Pezzicoli, Guillaume Charpiat, François Pascal Landes. Rotation-equivariant graph neural networks for learning glassy liquids representations. SciPost Physics, 2024, 16 (5), pp.136. ⟨10.21468/SciPostPhys.16.5.136⟩. ⟨hal-03868206v3⟩
  • Bruna Junqueira, Bruno Aristimunha, Sylvain Chevallier, Raphael de Camargo. A systematic evaluation of Euclidean alignment with deep learning for EEG decoding. Journal of Neural Engineering, 2024, 21 (3), pp.036038. ⟨10.1088/1741-2552/ad4f18⟩. ⟨hal-04677699⟩
  • Aurélien Decelle, Cyril Furtlehner, Alfonso de Jesús Navas Gómez, Beatriz Seoane. Inferring effective couplings with Restricted Boltzmann Machines. SciPost Physics, 2024, Scipost Physics, 16 (4), pp.095. ⟨10.21468/SciPostPhys.16.4.095⟩. ⟨hal-04885720⟩
  • Diego Delle Donne, Matthieu Kowalski, Leo Liberti. A Novel Integer Linear Programming Approach for Global L0 Minimization. Journal of Machine Learning Research, 2024, 24 (1), Art. no. 382, p.18322-18349. ⟨10.5555/3648699.3649081⟩. ⟨hal-04372309⟩
  • Maël Lefeuvre, Michael David Martin, Flora Jay, Marie-Claude Marsolier, Céline Bon. GRUPS-rs, a high-performance ancient DNA genetic relatedness estimation software relying on pedigree simulations. Human Population Genetics and Genomics, 2024, 4 (1), pp.0001. ⟨10.47248/hpgg2404010001⟩. ⟨hal-04709778⟩
  • Marco Baity-Jesi, Enrico Calore, Andrés Cruz, Luis Antonio Fernández, José Miguel Gil-Narvión, et al.. Multifractality in spin glasses. Proceedings of the National Academy of Sciences of the United States of America, In press, 121 (2), pp.e2312880120. ⟨10.1073/pnas.2312880120⟩. ⟨hal-04344056⟩
  • Céline Loot, Gael A Millot, Egill Richard, Eloi Littner, Claire Vit, et al.. Integron cassettes commonly integrate into bacterial genomes via widespread non-classical attG sites. Nature Microbiology, 2024, 9 (1), pp.228-240. ⟨10.1038/s41564-023-01548-y⟩. ⟨pasteur-04384854⟩
  • Giovanni Catania, Aurélien Decelle, Beatriz Seoane. The Copycat Perceptron: Smashing Barriers Through Collective Learning. Physical Review E , 2024, 109 (6), pp.065313. ⟨10.1103/PhysRevE.109.065313⟩. ⟨hal-04918895⟩
  • Marie-Constance Corsi, Pierpaolo Sorrentino, Denis P Schwartz, Nathalie George, Leonardo L. Gollo, et al.. Measuring Neuronal Avalanches to inform Brain-Computer Interfaces. iScience, 2024, 27 (1), pp.108734. ⟨10.1016/j.isci.2023.108734⟩. ⟨hal-04345847v2⟩
  • Romit Maulik, Romain Egele, Krishnan Raghavan, Prasanna Balaprakash. Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles. Physica D: Nonlinear Phenomena, 2023, 454, pp.133852. ⟨10.1016/j.physd.2023.133852⟩. ⟨hal-04219331⟩
  • Burak Yelmen, Aurélien Decelle, Leila Lea Boulos, Antoine Szatkownik, Cyril Furtlehner, et al.. Deep convolutional and conditional neural networks for large-scale genomic data generation. PLoS Computational Biology, 2023, 19 (10), pp.e1011584. ⟨10.1101/2023.03.07.530442⟩. ⟨hal-04244818⟩
  • Jazeps Medina-Tretmanis, Flora Jay, María C Ávila-Arcos, Emilia Huerta-Sanchez. Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure. Human Population Genetics and Genomics, 2023, pp.1-25. ⟨10.1101/2023.09.28.560049⟩. ⟨hal-04244011⟩
  • Amin Zammouri, Abdelaziz Ait Moussa, Sylvain Chevallier. Use of cognitive load measurements to design a new architecture of intelligent learning systems. Expert Systems with Applications, 2023, 237, pp.121253. ⟨10.1016/j.eswa.2023.121253⟩. ⟨hal-04350891⟩
  • Burak Yelmen, Flora Jay. An Overview of Deep Generative Models in Functional and Evolutionary Genomics. Annual Review of Biomedical Data Science, 2023, 6 (1), pp.173-189. ⟨10.1146/annurev-biodatasci-020722-115651⟩. ⟨hal-04243980⟩
  • Alessandra Carbone, Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane. Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 47 (2), pp.1309-1316. ⟨10.1109/TPAMI.2024.3495999⟩. ⟨hal-04344041⟩
  • Aurélien Decelle, Beatriz Seoane, Lorenzo Rosset. Unsupervised hierarchical clustering using the learning dynamics of restricted Boltzmann machines. Physical Review E , 2023, 108 (1), pp.014110. ⟨10.1103/PhysRevE.108.014110⟩. ⟨hal-04341820⟩
  • Ilaria Paga, Q. Zhai, Marco Baity-Jesi, Enrico Calore, Andrés Cruz, et al.. Superposition principle and nonlinear response in spin glasses. Physical Review B, 2023, 107, pp.214436. ⟨10.1103/PhysRevB.107.214436⟩. ⟨hal-04344051⟩
  • Alice Lacan, Michèle Sebag, Blaise Hanczar. GAN-based data augmentation for transcriptomics: survey and comparative assessment. Bioinformatics, 2023, 39 (Supplement_1), pp.i111-i120. ⟨10.1093/bioinformatics/btad239⟩. ⟨hal-04263316⟩
  • Viridiana Villa-Islas, Alan Izarraras-Gomez, Maximilian Larena, Elizabeth Mejía Perez Campos, Marcela Sandoval-Velasco, et al.. Demographic history and genetic structure in pre-Hispanic Central Mexico. Science, 2023, 380 (6645), pp.eadd6142. ⟨10.1126/science.add6142⟩. ⟨hal-04244008⟩
  • Adriano Barra, Giovanni Catania, Aurélien Decelle, Beatriz Seoane. Thermodynamics of bidirectional associative memories. Journal of Physics A: Mathematical and Theoretical, 2023, 56 (20), pp.205005. ⟨10.1088/1751-8121/accc60⟩. ⟨hal-04344065v2⟩
  • Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi, Lionel Mathelin, Marc Schoenauer. CD-ROM: Complementary Deep-Reduced Order Model. Computer Methods in Applied Mechanics and Engineering, 2023, 410, pp.115985. ⟨10.1016/j.cma.2023.115985⟩. ⟨hal-03846122⟩
  • Natalia Díaz-Rodríguez, Rūta Binkytė, Wafae Bakkali, Sannidhi Bookseller, Paola Tubaro, et al.. Gender and sex bias in COVID-19 epidemiological data through the lens of causality. Information Processing and Management, 2023, 60 (3), pp.103276. ⟨10.1016/j.ipm.2023.103276⟩. ⟨hal-03961804⟩
  • Marco Baity-Jesi, Enrico Calore, Andrea Cruz, Luis Fernandez, José Miguel Gil-Narvion, et al.. Memory and rejuvenation effects in spin glasses are governed by more than one length scale. Nature Physics, 2023, 19 (7), pp.978-985. ⟨10.1038/s41567-023-02014-6⟩. ⟨hal-04341897⟩
  • Isabelle Hoxha, Sylvain Chevallier, Matteo Ciarchi, Stefan Glasauer, Arnaud Delorme, et al.. Accounting for endogenous effects in decision-making with a non-linear diffusion decision model. Scientific Reports, 2023, 13 (1), pp.6323. ⟨10.1038/s41598-023-32841-9⟩. ⟨hal-04290041⟩
  • José Luis Molina, Paola Tubaro, Antonio Casilli, Antonio Santos-Ortega. Research Ethics in the Age of Digital Platforms. Science and Engineering Ethics, 2023, 29 (3), pp.17. ⟨10.1007/s11948-023-00437-1⟩. ⟨hal-04083115⟩
  • Anton Andreev, Grégoire H Cattan, Sylvain Chevallier, Quentin Barthélemy. pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry. Research Ideas and Outcomes, 2023, 9, pp.e101006. ⟨10.3897/rio.9.e101006⟩. ⟨hal-04040814⟩
  • Jérémy Guez, Guillaume Achaz, François Bienvenu, Jean Cury, Bruno Toupance, et al.. Cultural transmission of reproductive success impacts genomic diversity, coalescent tree topologies and demographic inferences. Genetics, 2023, 223 (4), pp.iyad007. ⟨10.1093/genetics/iyad007⟩. ⟨hal-03875721⟩
  • Cyril Furtlehner. Free Dynamics of Feature Learning Processes. Journal of Statistical Physics, 2023, Journal of Statistical Physics, 190 (51), pp.42. ⟨10.1007/s10955-022-03064-5⟩. ⟨hal-03878500v2⟩
  • Sabrina Amrouche, Laurent Basara, Paolo Calafiura, Dmitry Emeliyanov, Victor Estrade, et al.. The Tracking Machine Learning challenge : Throughput phase. Computing and Software for Big Science, 2023, 7 (1), pp.1. ⟨10.1007/s41781-023-00094-w⟩. ⟨hal-03159824v2⟩
  • Théophile Sanchez, Erik Madison Bray, Pierre Jobic, Jérémy Guez, Anne-Catherine Letournel, et al.. dnadna: a deep learning framework for population genetics inference. Bioinformatics, 2023, 39 (1), pp.btac765. ⟨10.1093/bioinformatics/btac765⟩. ⟨hal-03352910v4⟩
  • Tony Bonnaire, Joseph Kuruvilla, Nabila Aghanim, Aurélien Decelle. Cosmology with cosmic web environments II. Redshift-space auto and cross power spectra. Astronomy & Astrophysics - A&A, 2023, 674, pp.A150. ⟨10.1051/0004-6361/202245626⟩. ⟨hal-03922267⟩
  • Sarah Hartley, Guillaume Bao, Ashley Russo, Marine Zagdoun, Sylvain Chevallier, et al.. Self-administered non-invasive vagus nerve stimulation therapy for severe pharmacoresistant restless legs syndrome: outcomes at 6 months. Journal of Sleep Research, 2023, 33, pp.e14066. ⟨10.1111/jsr.14066⟩. ⟨hal-04258081⟩
  • Isaac Overcast, Guillaume Achaz, R. Aguilée, Carmelo Andújar, Paula Arribas, et al.. Towards a genetic theory of island biogeography: Inferring processes from multidimensional community‐scale data. Global Ecology and Biogeography, 2023, 32, pp.4 - 23. ⟨10.1111/geb.13604⟩. ⟨inserm-04270149⟩
  • Maria Sayu Yamamoto, Khadijeh Sadatnejad, Toshihisa Tanaka, Md Rabiul Islam, Frédéric Dehais, et al.. Modeling complex EEG data distribution on the Riemannian manifold toward outlier detection and multimodal classification. IEEE Transactions on Biomedical Engineering, In press, 72 (2), pp.377 - 387. ⟨10.1109/TBME.2023.3295769⟩. ⟨hal-04181396⟩
  • Sarah Hartley, Guillaume Bao, Marine Zagdoun, Sylvain Chevallier, Frédéric Lofaso, et al.. Noninvasive Vagus Nerve Stimulation: A New Therapeutic Approach for Pharmacoresistant Restless Legs Syndrome. Neuromodulation, 2022, 26 (3), pp.629-637. ⟨10.1016/j.neurom.2022.10.046⟩. ⟨hal-03921967⟩
  • Aurélien Decelle. Fundamental problems in Statistical Physics XV: Lecture on Machine Learning. Physica A: Statistical Mechanics and its Applications, 2022, pp.128154. ⟨10.1016/j.physa.2022.128154⟩. ⟨hal-03795587⟩
  • Karan Bhanot, Joseph Pedersen, Isabelle Guyon, Kristin P Bennett. Investigating synthetic medical time-series resemblance. Neurocomputing, 2022, 494, pp.368-378. ⟨10.1016/j.neucom.2022.04.097⟩. ⟨hal-04465658⟩
  • Zhen Xu, Sergio Escalera, Adrien Pavao, Magali Richard, Wei-Wei Tu, et al.. Codabench: Flexible, Easy-to-Use and Reproducible Meta-Benchmark Platform. Patterns, 2022, 3 (7), pp.100543. ⟨10.1016/j.patter.2022.100543⟩. ⟨hal-03374222v4⟩
  • Tony Bonnaire, Nabila Aghanim, Joseph Kuruvilla, Aurélien Decelle. Cosmology with cosmic web environments. Astronomy & Astrophysics - A&A, 2022, 661, pp.A146. ⟨10.1051/0004-6361/202142852⟩. ⟨hal-03677762⟩
  • Consortium Icubam, Laurent Bonnasse-Gahot, Maxime Dénès, Gabriel Dulac-Arnold, Sertan Girgin, et al.. ICU Bed Availability Monitoring and analysis in the Grand Est region of France during the COVID-19 epidemic. Statistique et Société, 2022, 10 (1), pp.19-36. ⟨10.1101/2020.05.18.20091264⟩. ⟨hal-02620018⟩
  • Jean Cury, Benjamin C Haller, Guillaume Achaz, Flora Jay. Simulation of bacterial populations with SLiM. Peer Community Journal, 2022, 2, pp.e7. ⟨10.24072/pcjournal.72⟩. ⟨hal-03152153v3⟩
  • Paola Tubaro, Marion Coville, Clément Le Ludec, Antonio A Casilli. Hidden inequalities: the gendered labour of women on micro-tasking platforms. Internet Policy Review, 2022, The gender of the platform economy, 11 (1), ⟨10.14763/2022.1.1623⟩. ⟨hal-03551747⟩
  • Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, et al.. Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking. IEEE Transactions on Evolutionary Computation, 2022, 26 (3), pp.490-500. ⟨10.1109/TEVC.2021.3108185⟩. ⟨hal-03154019⟩
  • Paola Tubaro. Learners in the loop: hidden human skills in machine intelligence. Sociologia del Lavoro, 2022, 163, pp.110-129. ⟨10.3280/SL2022-163006⟩. ⟨hal-03787017⟩
  • Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane. Learning a Restricted Boltzmann Machine using biased Monte Carlo sampling. SciPost Physics, In press, 14 (3), pp.032. ⟨10.21468/SciPostPhys.14.3.032⟩. ⟨hal-03795598⟩
  • Cyril Furtlehner, Jean-Marc Lasgouttes, Alessandro Attanasi, Marco Pezzulla, Guido Gentile. Short-term Forecasting of Urban Traffic using Spatio-Temporal Markov Field. IEEE Transactions on Intelligent Transportation Systems, 2022, 23 (8), pp.10858-10867. ⟨10.1109/TITS.2021.3096798⟩. ⟨hal-03285664⟩
  • Sylvain Chevallier, Marie Constance Corsi, Florian Yger, Fabrizio de Vico Fallani. Riemannian geometry for combining functional connectivity metrics and covariance in BCI. Software Impacts, 2022, 12, pp.100254. ⟨10.1016/j.simpa.2022.100254⟩. ⟨hal-03772666⟩
  • Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon, David Lopez-Paz, Michèle Sebag. Structural Agnostic Modeling: Adversarial Learning of Causal Graphs. Journal of Machine Learning Research, 2022, 23 (219), pp.1-62. ⟨hal-03831338⟩
  • Aurélien Decelle, Tony Bonnaire, Nabila Aghanim. Regularization of Mixture Models for Robust Principal Graph Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, pp.1-1. ⟨10.1109/TPAMI.2021.3124973⟩. ⟨hal-03477742⟩
  • Aurelien Decelle, Sungmin Hwang, Jacopo Rocchi, Daniele Tantari. Inverse problems for structured datasets using parallel TAP equations and restricted Boltzmann machines. Scientific Reports, 2021, 11 (1), pp.19990. ⟨10.1038/s41598-021-99353-2⟩. ⟨hal-04452550⟩
  • Paola Tubaro. Disembedded or Deeply Embedded? A Multi-Level Network Analysis of Online Labour Platforms. Sociology, 2021, 55 (5), pp.927-944. ⟨10.1177/0038038520986082⟩. ⟨hal-03127861⟩
  • A Decelle, Cyril Furtlehner. Exact Training of Restricted Boltzmann Machines on Intrinsically Low Dimensional Data. Physical Review Letters, 2021, pp.158303. ⟨10.1103/PhysRevLett.127.158303⟩. ⟨hal-03432350⟩
  • Paola Tubaro, Louise Ryan, Antonio A. Casilli, Alessio D’angelo. Social network analysis: New ethical approaches through collective reflexivity. Introduction to the special issue of Social Networks. Social Networks, 2021, Recent ethical challenges in social network analysis, 67, pp.1-8. ⟨10.1016/j.socnet.2020.12.001⟩. ⟨hal-03090287⟩
  • Paola Tubaro. Whose results are these anyway? Reciprocity and the ethics of “giving back” after social network research. Social Networks, 2021, Recent ethical challenges in social network analysis, 67, pp.65-73. ⟨10.1016/j.socnet.2019.10.003⟩. ⟨hal-02360709⟩
  • Marion Ullmo, Aurélien Decelle, Nabila Aghanim. Encoding large scale cosmological structure with Generative Adversarial Networks. Astronomy & Astrophysics - A&A, 2021, 651, pp.A46. ⟨10.1051/0004-6361/202039866⟩. ⟨hal-03034838⟩
  • Zhengying Liu, Adrien Pavao, Zhen Xu, Sergio Escalera, Fabio Ferreira, et al.. Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43 (9), pp.3108 - 3125. ⟨10.1109/TPAMI.2021.3075372⟩. ⟨hal-02957135v5⟩
  • Philippe Caillou, Jonas Renault, Jean-Daniel Fekete, Anne-Catherine Letournel, Michèle Sebag. Cartolabe: A Web-Based Scalable Visualization of Large Document Collections. IEEE Computer Graphics and Applications, 2021, 41 (2), pp.76--88. ⟨10.1109/MCG.2020.3033401⟩. ⟨hal-02499006⟩
  • Pauline Bennet, Perrine Juillet, Sara Ibrahim, Vincent Berthier, Mamadou Aliou Barry, et al.. Analysis and fabrication of antireflective coating for photovoltaics based on a photonic-crystal concept and generated by evolutionary optimization. Physical Review B, 2021, 103 (12), pp.125135. ⟨10.1103/PhysRevB.103.125135⟩. ⟨hal-03172152⟩
  • Rahul N Chacko, François P. Landes, Giulio Biroli, Olivier Dauchot, Andrea J Liu, et al.. Elastoplasticity Mediates Dynamical Heterogeneity Below the Mode-Coupling Temperature. Physical Review Letters, 2021, 127 (4), pp.048002. ⟨10.1103/PhysRevLett.127.048002⟩. ⟨hal-03345449⟩
  • Burak Yelmen, Aurélien Decelle, Linda Ongaro, Davide Marnetto, Corentin Tallec, et al.. Creating artificial human genomes using generative neural networks. PLoS Genetics, 2021, 17 (2), pp.e1009303. ⟨10.1371/journal.pgen.1009303⟩. ⟨hal-03149930⟩
  • Michele Alessandro Bucci, Stefania Cherubini, Jean-Christophe Loiseau, Jean-Christophe Robinet. Influence of freestream turbulence on the flow over a wall roughness. Physical Review Fluids, 2021, 6 (6), pp.063903. ⟨10.1103/physrevfluids.6.063903⟩. ⟨hal-03268719⟩
  • Aurélien Decelle, Tony Bonnaire, Nabila Aghanim. Cascade of phase transitions for multiscale clustering. Physical Review E , 2021, 103 (1), pp.012105. ⟨10.1103/PhysRevE.103.012105⟩. ⟨hal-03477663⟩

Conference papers105 documents

  • Johanne Cohen, Emmanuel Goutierre, Hayg Guler, Fatios Kapotos, Sida-Bastien Li, et al.. Modelling Dynamical Systems: Learning ODEs with No Internal ODE Resolution. 18th International Conference, RP 2024, Sep 2025, Vienne, Austria. pp.221-237, ⟨10.1007/978-3-031-72621-7_15⟩. ⟨hal-05240753⟩
  • Nilo Schwencke, Cyriaque Rousselot, Alena Shilova, Cyril Furtlehner. AMSTRAMGRAM : Adaptive Multi-cutoff Strategy Modification for ANaGRAM. ENUMATH2025 : MS31 – Geometric Optimization Methods for Scientific Machine Learning, Marius Zeinhofer; Johannes Müller, Sep 2025, Heidelberg, Germany. ⟨hal-05245453⟩
  • Dylan Sechet, Matthieu Kowalski, Samy Mokhtari, Bruno Torrésani. Revisiting CHAMPAGNE: Sparse Bayesian Learning as Reweighted Sparse Coding. SampTA 2025 - International Conference on Sampling Theory and Applications, Jul 2025, Vienna, Austria. ⟨hal-05130740⟩
  • Thibault de Surrel, Fabien Lotte, Sylvain Chevallier, Florian Yger. Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices. ICML 2025 - 42nd International Conference on Machine Learning, Jul 2025, Vancouver, Canada. ⟨hal-05158268⟩
  • Guillaume Attuel, Matthieu Kowalski. Disentangling Myth from Reality: A Plea for exploring New Avenues. QIP25 - Quantum Information and Probability: from Foundations to Engineering, Andrei Khrennikov, Jun 2025, Vaxjö, Sweden. ⟨hal-05114054v2⟩
  • Nicolas Atienza, Christophe Labreuche, Johanne Cohen, Michèle Sebag. Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach. 13th International Conference on Learning Representations - ICLR 2025, Apr 2025, Singapore, Singapore. ⟨hal-04922382⟩
  • Nicolas Bereux, Aurélien Decelle, Cyril Furtlehner, Lorenzo Rosset, Beatriz Seoane. Fast training and sampling of Restricted Boltzmann Machines. 13th International Conference on Learning Representations - ICLR 2025, Apr 2025, Singaour, Singapore. ⟨hal-04885777⟩
  • Nilo Schwencke, Cyril Furtlehner. ANAGRAM: a natural gradient relative to adapted model for efficient PINNS learning. 13th International Conference on Learning Representations - ICLR 2025, Apr 2025, Singapour, Singapore. ⟨hal-04918272⟩
  • Stella Douka, Manon Verbockhaven, Théo Rudkiewicz, Stéphane Rivaud, François P. Landes, et al.. Growth strategies for arbitrary DAG neural architectures. ESANN 2025 - 33th European Symposium on Artificial Neural Networks, Apr 2025, Bruges, Belgium. ⟨hal-04902059v2⟩
  • Shuyu Dong, Michèle Sebag, Kento Uemura, Akito Fujii, Shuang Chang, et al.. DCDILP: a distributed learning method for large-scale causal structure learning. AAAI 25 - The 39th Annual AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, Feb 2025, Philadelphia (PA), United States. ⟨hal-04710846⟩
  • Mouadh Yagoubi, David Danan, Milad Leyli-Abadi, Jean-Patrick Brunet, Maroua Gmati, et al.. NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design. NeurIPS 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨hal-04869170⟩
  • Apolline Mellot, Antoine Collas, Sylvain Chevallier, Alexandre Gramfort, Denis Engemann. Geodesic optimization for predictive shift adaptation on EEG data. NeurIPS 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨hal-04902523⟩
  • Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle, Beatriz Seoane. Cascade of phase transitions in the training of Energy-based models. NeurIPS 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. ⟨10.48550/arXiv.2405.14689⟩. ⟨hal-04897693⟩
  • Cyriaque Rousselot, Olivier Allais, Philippe Caillou, Julia Mink, Florian Yger. Assessing Impact of Pesticide Exposure on Child Health using Large-Scale Data Integration and Modelling​. Workshop 2024 - Qualité de l’Air, Agriculture et Santé Humaine, Nov 2024, Saint-Rémy-lès-Chevreuses, France. ⟨hal-04991175⟩
  • Sébastien Velut, Sylvain Chevallier, Marie-Constance Corsi, Frédéric Dehais. Deep Riemannian Neural Architectures for Domain Adaptation in Burst cVEP-based Brain Computer Interface. ESANN 2024 - 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2024, Bruges, Belgium. pp.571-576, ⟨10.14428/esann/2024.ES2024-112⟩. ⟨hal-04720928⟩
  • Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat. Time and State Dependent Neural Delay Differential Equations. ML-DE@ECAI 2024 : Machine Learning Meets Differential Equations: From Theory to Applications, Sep 2024, Santiago de compostela, Galicia, Spain. ⟨hal-04794450⟩
  • Alice Lacan, Blaise Hanczar, Michele Sebag. Frugal Generative Modeling for Tabular Data. ECML PKDD 2024 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2024, Vilnius, Lithuania. pp.55--72, ⟨10.1007/978-3-031-70371-3_4⟩. ⟨hal-04705131⟩
  • Eva Boguslawski, Alessandro Leite, Benjamin Donnot, Matthieu Dussartre, Marc Schoenauer. Emulation of Zonal Controllers for the Power System Transport Problem. ML4SPS 2024 - Machine Learning for Sustainable Power Systems ECML 2024 Workshop, European Conference of Machine Learning, Sep 2024, Vilnius, Lithuania. ⟨hal-04924271⟩
  • Dylan Sechet, Francesca Bugiotti, Matthieu Kowalski, Edouard D’hérouville, Filip Langiewicz. A Hierarchical Deep Learning Approach for Minority Instrument Detection. DAFx 2024 - the 27th International Conference on Digital Audio Effects, Sep 2024, Guildford Surrey, United Kingdom. ⟨hal-04793160⟩
  • Gustavo H Rodrigues, Bruno Aristimunha, Sylvain Chevallier, Raphael Y de Camargo. Combining Euclidean Alignment and Data Augmentation for BCI decoding. EUSIPCO 2024 - 32nd European Signal Processing Conference, European Signal Processing Conference (EUSIPCO), Aug 2024, Lyon, France. ⟨10.48550/arXiv.2405.14994⟩. ⟨hal-04743791⟩
  • Thibault de Surrel, Sylvain Chevallier, Fabien Lotte, Florian Yger. Averaging trajectories on the manifold of symmetric positive definite matrices. EUSIPCO 2024 - 32nd European Signal Processing Conference, Aug 2024, Lyon, France. ⟨10.23919/EUSIPCO63174.2024.10715315⟩. ⟨hal-04708878⟩
  • Apolline Mellot, Antoine Collas, Sylvain Chevallier, Denis Engemann, Alexandre Gramfort. Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets. EUSIPCO 2024 - 32nd European Signal Processing Conference, Aug 2024, Lyon, France. ⟨10.48550/arXiv.2403.15415⟩. ⟨hal-04716030⟩
  • Audrey Poinsot, Alessandro Leite, Nicolas Chesneau, Michele Sebag, Marc Schoenauer. Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. IJCAI 2024 - Survey Track, Aug 2024, Jeju, South Korea. pp.8207-8215, ⟨10.24963/ijcai.2024/907⟩. ⟨hal-04706985⟩
  • Nicolas Atienza, Roman Bresson, Cyriaque Rousselot, Philippe Caillou, Johanne Cohen, et al.. Cutting the Black Box: Conceptual Interpretation of a Deep Neural Net with Multi-Modal Embeddings and Multi-Criteria Decision Aid. IJCAI 2024, 33rd International Joint Conference on Artificial Intelligence, Aug 2024, Jeju, South Korea. pp.3669-3678, ⟨10.24963/ijcai.2024/406⟩. ⟨hal-04728875⟩
  • Eva Boguslawski, Alessandro Leite, Matthieu Dussartre, Benjamin Donnot, Marc Schoenauer. Emulation of Zonal Controllers for the Power System Transport Problem. RJCIA - PFIA 2024 - 23èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle, Jul 2024, La Rochelle, France. ⟨hal-04942704⟩
  • Paulo Henrique Couto, Quang Phuoc Ho, Nageeta Kumari, Benedictus Kent Rachmat, Thanh Gia Hieu Khuong, et al.. RelevAI-Reviewer: A Benchmark on AI Reviewers for Survey Paper Relevance. CAp 2024 - Conférence sur l'Apprentissage Automatique, Jul 2024, Lille, France. ⟨hal-04608255⟩
  • Matthieu Nastorg, Jean-Marc Gratien, Thibault Faney, Michele Alessandro Bucci, Guillaume Charpiat, et al.. Multi-Level GNN Preconditioner for Solving Large Scale Problems. 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May 2024, San Francisco (CA, USA), United States. pp.486-495, ⟨10.1109/IPDPSW63119.2024.00101⟩. ⟨hal-04447099⟩
  • Jonathan Xu, Bruno Aristimunha, Max Emanuel Feucht, Emma Qian, Charles Liu, et al.. Alljoined1 -A dataset for EEG-to-Image decoding. Workshop Data Curation and Augmentation in Medical Imaging at 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, May 2024, Seattle, United States. ⟨10.48550/arXiv.2404.05553⟩. ⟨hal-04743819⟩
  • Jean-Baptiste Malagnoux, Matthieu Kowalski. From Convolutional Sparse Coding To *-NMF Factorization of Time-Frequency Coefficients. ICASSP 2024 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2024, Séoul, South Korea. pp.5530-5534, ⟨10.1109/ICASSP48485.2024.10447466⟩. ⟨hal-04608586⟩
  • Bruno Aristimunha, Raphael Yokoingawa de Camargo, Sylvain Chevallier, Adam G. Thomas, Oeslle Lucena, et al.. Synthetic Sleep EEG Signal Generation using Latent Diffusion Models. DGM4H 2023 - 1st Workshop on Deep Generative Models for Health at NeurIPS 2023, Dec 2023, New orleans, United States. ⟨hal-04350867⟩
  • Emmanuel Goutierre, Christelle Bruni, Johanne Cohen, Hayg Guler, Michèle Sebag. Physics-aware modelling of an accelerated particle cloud. MLPS 2023 - Machine Learning and the Physical Sciences Workshop 23023 - At the 37th conference on Neural Information Processing Systems (NeurIPS), Dec 2023, New Orleans, United States. ⟨hal-04396175⟩
  • Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Burak Yelmen, Flora Jay. Towards creating longer genetic sequences with GANs: Generation in principal component space. MLCB 2023 - 18th Conference on Machine Learning in Computational Biology, Nov 2023, Seattle, United States. ⟨hal-04419057⟩
  • Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi, Lionel Mathelin, Marc Schoenauer. CD-ROM: Complemented Deep-Reduced Order Model. MORTech 2023 - 6th International Workshop on Model Order Reduction, Nov 2023, Saclay, France. ⟨hal-04406567⟩
  • Romain Egele, Isabelle Guyon, Venkatram Vishwanath, Prasanna Balaprakash. Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization. eS 2023 - 19th IEEE International Conference on e-Science, Oct 2023, Limassol, Cyprus. pp.1-10, ⟨10.1109/e-Science58273.2023.10254839⟩. ⟨hal-04219312⟩
  • Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash. Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?. ESANN 2023 - 31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Oct 2023, Bruges / Hybrid, Belgium. ⟨hal-04219301⟩
  • Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, et al.. Fairness in job recommendations: estimating, explaining, and reducing gender gaps. AEQUITAS 2023 - First AEQUITAS Workshop on Fairness and Bias in AI | co-located with ECAI 2023, Oct 2023, Krakow, Poland. ⟨hal-04438512⟩
  • Thanh Gia Hieu Khuong, Benedictus Kent Rachmat. Auto-survey Challenge. JDSE 2023 - 8th Junior Conference on Data Science and Engineering, Sep 2023, Orsay, France. ⟨hal-04206578v2⟩
  • Pierre Barbault, Matthieu Kowalski, Charles Soussen. Marginal MAP estimation of a Bernoulli-Gaussian signal: continuous relaxation approach. EUSIPCO 2023 - the 31st European Signal Processing Conference, Sep 2023, Helsinki, Finland. pp.1833-1837, ⟨10.23919/EUSIPCO58844.2023.10289911⟩. ⟨hal-04383978⟩
  • Maria Sayu Yamamoto, Apolline Mellot, Sylvain Chevallier, Fabien Lotte. Novel SPD matrix representations considering cross-frequency coupling for EEG classification using Riemannian geometry. EUSIPCO 2023 - the 31st European Signal Processing Conference, Sep 2023, Helsinki, Finland. ⟨10.23919/EUSIPCO58844.2023.10290043⟩. ⟨hal-04131609⟩
  • Sylvain Chevallier, Yann Thanwerdas. Stratified Riemannian geometry for frugal learning with brain signals. Geometric Science of Information, Franck Nielsen; Frédéric Barbaresco, Aug 2023, Saint-Malo, France. ⟨hal-04935637⟩
  • Florent Michel, Benoît Malézieux, Matthieu Kowalski, Thomas Moreau. L'entropie comme mesure de difficulté des problèmes inverses. GRETSI'23 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France. pp.1013-1016. ⟨hal-05132642⟩
  • Pierre Barbault, Matthieu Kowalski, Charles Soussen. Estimation du MAP Marginal d'un signal Bernoulli-Gaussien: une approche par relaxation continue. GRETSI 2023 - XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France. pp.1-4. ⟨hal-04383981⟩
  • Guillaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, et al.. Toward Job Recommendation for All. IJCAI 2023 - The 32nd International Joint Conference on Artificial Intelligence, Aug 2023, Macau, China. pp.5906-5914, ⟨10.24963/ijcai.2023/655⟩. ⟨hal-04245528⟩
  • Alessandra Carbone, Aurélien Decelle, Lorenzo Rosset, Beatriz Seoane. Fast and Functional structured data generator. ICML 2023 - Workshop on Structured Probabilistic Inference & Generative Modeling, Jul 2023, Honolulu, United States. ⟨hal-04342214⟩
  • Elisabeth Agoritsas, Giovanni Catania, Aurélien Decelle, Beatriz Seoane. Explaining the effects of non-convergent sampling in the training of Energy-Based Models. ICML 2023 - 40th International Conference on Machine Learning, Jul 2023, Honolulu (Hawaii), United States. ⟨hal-04344101⟩
  • Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, et al.. Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals. ICML 2023 - 40th International Conference on Machine Learning, Jul 2023, Honololu, United States. pp.1-29, ⟨10.48550/arXiv.2303.05798⟩. ⟨hal-04250921⟩
  • Mathurin Videau, Nickolai Knizev, Alessandro Leite, Marc Schoenauer, Olivier Teytaud. Interactive Latent Diffusion Model. GECCO 2023 - Genetic and Evolutionary Computation Conference, ACM SIGEVO, Jul 2023, Lisbon, Portugal. pp.586-596, ⟨10.1145/3583131.3590471⟩. ⟨hal-04570089⟩
  • Guillaume Bied, Elia Perennes, Solal Nathan, Victor Naya, Philippe Caillou, et al.. RECTO : REcommandation diminuant la Congestion par Transport Optimal. APIA 2023 - 9ème Conférence Nationale sur les Applications Pratiques de l’Intelligence Artificielle, AFIA-Association Française pour l'Intelligence Artificielle; ICube-laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie, Jul 2023, Strasbourg, France. pp.89-98. ⟨hal-04158566⟩
  • Haozhe Sun, Isabelle Guyon. Modularity in Deep Learning: A Survey. SAI 2023 - Intelligent Computing Conference, Jun 2023, London, United Kingdom. pp.561-595, ⟨10.1007/978-3-031-37963-5_40⟩. ⟨hal-04224278⟩
  • Haozhe Sun, Isabelle Guyon, Felix Mohr, Hedi Tabia. RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network. IJCNN 2023 - International Joint Conference on Neural Networks, Jun 2023, Gold Coast, Australia. pp.1-9, ⟨10.1109/IJCNN54540.2023.10191770⟩. ⟨hal-04224281⟩
  • Sylvain Chevallier, Quentin Barthélemy, Raphaëlle Bertrand-Lalo, Pierre Clisson. Early stopping strategies for P300 speller with Bayesian accumulation of Riemannian probabilities. BCI 2023 - 10th International Brain-Computer Interface Meeting, BCI Society, Jun 2023, Bruxelles, Belgium. ⟨10.3217/978-3-85125-962-9-155⟩. ⟨hal-04677800⟩
  • Marie-Constance Corsi, Sylvain Chevallier, Fabrizio de Vico Fallani, Florian Yger. Empirical evaluation on multiple BCI datasets of the functional connectivity ensemble (FUCONE) method. BCI 2023 - 10th International Brain-Computer Interface Meeting, BCI Society, Jun 2023, Bruxelles, Belgium. ⟨10.3217/978-3-85125-962-9-24⟩. ⟨hal-04677809⟩
  • Marie-Constance Corsi, Sylvain Chevallier, Fabrizio de Vico Fallani, Florian Yger. Ensemble of Riemannian Classifiers for Multimodal Data: FUCONE Approach for M/EEG Data. ISBI 2023 - IEEE International Symposium on Biomedical Imaging, Apr 2023, Cartagena de Indias, Colombia. ⟨hal-04140126⟩
  • Alessandro Leite, Marc Schoenauer. Memetic Semantic Genetic Programming for Symbolic Regression. 26th EuroGP - Part of EvoStar 2023, Species Society, Apr 2023, Brno, Czech Republic. pp.198-212, ⟨10.1007/978-3-031-29573-7_13⟩. ⟨hal-04563511⟩
  • Thibault Monsel, Lionel Mathelin, Onofrio Semeraro, Guillaume Charpiat. End-to-end learning of dynamical systems with the Mori-Zwanzig formalism. SIAM Conference on Computational Science and Engineering (CSE23), Feb 2023, Amsterdam, Netherlands. ⟨hal-04406551⟩
  • Guillaume Bied, Solal Nathan, Elia Perennes, Christophe Gaillac, Philippe Caillou, et al.. Using Data from job seekers, job offers and past hirings to learn a Job Recommender System: the VADORE Project. AI for HR and Public Employment Services, Feb 2023, Ghent, Belgium. ⟨hal-04025000⟩
  • Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Solal Nathan, Philippe Caillou, et al.. Gender fairness in job recommendation: a case study. AI for HR and Public Employment Services, Feb 2023, Ghent, Belgium. ⟨hal-04025006⟩
  • Georgios Zervakis, Emmanuel Vincent, Miguel Couceiro, Marc Schoenauer, Esteban Marquer. An analogy based approach for solving target sense verification. NLPIR 2022 - 6th International Conference on Natural Language Processing and Information Retrieval, Dec 2022, Bangkok, Thailand. ⟨hal-03792071⟩
  • Gaëtan Serré, Eva Boguslawski, Benjamin Donnot, Adrien Pavão, Isabelle Guyon, et al.. Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design. SSCI 2022 - IEEE Symposium Series on Computational Intelligence, IEEE, Dec 2022, Singapour, Singapore. ⟨hal-03726294v2⟩
  • Matthieu Nastorg, Marc Schoenauer, Guillaume Charpiat, Thibault Faney, Jean-Marc Gratien, et al.. DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations). Machine Learning and the Physical Sciences workshop, NeurIPS 2022, Dec 2022, New-Orleans, United States. ⟨hal-03861311⟩
  • Matthieu Nastorg, Marc Schoenauer, Guillaume Charpiat, Thibault Faney, Jean-Marc Gratien, et al.. DS-GPS : A Deep Statistical Graph Poisson Solver. NeurIPS 2022 - Machine Learning and the Physical Sciences, workshop, Dec 2022, New-Orleans, United States. ⟨hal-03864015⟩
  • Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, et al.. Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification. NeurIPS 2022 - 36th Conference on Neural Information Processing Systems - Track on Datasets and Benchmarks, NeurIPS, Nov 2022, New Orleans, United States. ⟨hal-03991982⟩
  • Wenzhuo Liu, Mouadh Yagoubi, David Danan, Marc Schoenauer. Multi-Fidelity Transfer Learning for accurate data-based PDE approximation. NeurIPS 2022 - Workshop on Machine Learning and the Physical Sciences, Nov 2022, New Orleans, United States. ⟨hal-03878200v2⟩
  • Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup, Sylvain Chevallier, Vinay Jayaram, et al.. 2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. NeurIPS, Nov 2022, Nouvelle Orleans, United States. ⟨hal-04677636⟩
  • Taha Houda, Jinan Charafeddine, Hani Hamdan, Sylvain Chevallier. On Path Planning and Optimization Strategies: Toward Embedded Road Applications. IEEE International Conference on Smart Systems and Power Management 2022, Nov 2022, Beirut, Lebanon. pp.197-202, ⟨10.1109/IC2SPM56638.2022.9988830⟩. ⟨hal-03967576⟩
  • Adrien Pavao, Zhengying Liu, Isabelle Guyon. Filtering participants improves generalization in competitions and benchmarks. ESANN 2022 - European Symposium on Artificial Neural Networks, Oct 2022, Bruges, Belgium. ⟨hal-03869648⟩
  • Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera, Chaoyu Guan, et al.. NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results. Meta-Knowledge Transfer/Communication in Different Systems, Sep 2022, Grenoble, France. ⟨hal-03765151⟩
  • Guillaume Bied, Solal Nathan, Elia Pérennes, Victor Alfonso Naya, Philippe Caillou, et al.. Recommender system in a non-stationary context: recommending job ads in pandemic times. FEAST workshop ECML-PKDD 2022, Sep 2022, Grenoble, France. ⟨hal-03831247⟩
  • Shuyu Dong, Michèle Sebag. From graphs to DAGs: a low-complexity model and a scalable algorithm. ECML-PKDD 2022 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2022, Grenoble, France. ⟨hal-03798964⟩
  • Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, et al.. HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization. CLUSTER 2022 - IEEE International Conference on Cluster Computing (CLUSTER), Sep 2022, Heidelberg, Germany. pp.381-393, ⟨10.1109/CLUSTER51413.2022.00049⟩. ⟨hal-03864478⟩
  • Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, et al.. AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. 26TH International Conference on Pattern Recognition, Aug 2022, Montréal, Canada. pp.1908-1914, ⟨10.1109/ICPR56361.2022.9956231⟩. ⟨hal-03518597⟩
  • Manh Hung Nguyen, Lisheng Sun-Hosoya, Nathan Grinsztajn, Isabelle Guyon. Meta-learning from Learning Curves: Challenge Design and Baseline Results. IJCNN 2022 - International Joint Conference on Neural Networks, Jul 2022, Padua, Italy. pp.1-8, ⟨10.1109/IJCNN55064.2022.9892534⟩. ⟨hal-03740118⟩
  • Vianney Taquet, Vincent Blot, Thomas Morzadec, Louis Lacombe, Nicolas J-B. Brunel. MAPIE: an open-source library for distribution-free uncertainty quantification. ICML 2022 - Workshop Distribution Free and Uncertainty Quantification ICML, Jul 2022, Baltimore / Hybrid, United States. ⟨hal-05232300⟩
  • Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi, Lionel Mathelin, Thibault Dairay, et al.. Continuous Methods : Adaptively intrusive reduced order model closure. ICML 2022 - Workshop Continuous time methods for machine learning, Jul 2022, Baltimore, United States. ⟨hal-03879332⟩
  • Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi, Lionel Mathelin, Marc Schoenauer. CD-ROM -- Complementary Deep - Reduced Order Model. IUTAM Symposium on Data-driven modeling and optimization in fluid mechanics 2022, Jun 2022, Aarhus, Denmark. ⟨hal-04405482⟩
  • Marc Schoenauer, Nadine Hilgert, Roman Ikonicoff, Jean-Pilippe Cointet. Table ronde - Intelligence artificielle : quels bouleversements pour les scientifiques, quels impacts dans les rapports entre science et société ?. Cycle Recherche en société #4 - Intelligence Artificielle, MSH Sud; Cirad, May 2022, Montpellier, France. ⟨hal-04190281⟩
  • Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michèle Sebag, Marc Schoenauer. Learning Meta-features for AutoML. ICLR 2022 - International Conference on Learning Representations (spotlight), Apr 2022, Virtual, United States. ⟨hal-03583789v2⟩
  • Mathurin Videau, Alessandro Ferreira Leite, Olivier Teytaud, Marc Schoenauer. Multi-Objective Genetic Programming for Explainable Reinforcement Learning. EUROGP 2022 - 25th European Conference on Genetic Programming, Apr 2022, Madrid, Spain. pp.278-293, ⟨10.1007/978-3-031-02056-8_18⟩. ⟨hal-03886307⟩
  • Joseph Pedersen, Rafael Muñoz Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, et al.. LTU Attacker for Membership Inference. Third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22), Feb 2022, virtual, France. ⟨hal-03522633v2⟩
  • Asanee Kawtrakul, Hutchatai Chanlekha, Kitsana Waiyamai, Thanapat Kangkachit, Laurent d'Orazio, et al.. Towards Data-and-Innovation Driven Sustainable and Productive Agriculture: BIO-AGRI-WATCH as a Use Case Study. Workshop on Smart Farming, Precision Agriculture, and Supply Chain (SmartFarm@BigData), Dec 2021, Virtuelle, France. ⟨hal-03522308⟩
  • Adrien Pavao, Isabelle Guyon, Nachar Stéphane, Fabrice Lebeau, Martin Ghienne, et al.. Aircraft Numerical "Twin": A Time Series Regression Competition. ICMLA 2021 - 20th IEEE International Conference on Machine Learning and Applications., Dec 2021, Pasadena / Virtual, United States. ⟨10.1109/ICMLA52953.2021.00075⟩. ⟨hal-03463307v3⟩
  • Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane. Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann Machines. NeurIPS 2021, Dec 2021, Vancouver, United States. ⟨hal-03518796⟩
  • Haozhe Sun, Wei-Wei Tu, Isabelle Guyon. OmniPrint: A Configurable Printed Character Synthesizer. Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1), Dec 2021, Online, France. ⟨hal-03506905⟩
  • Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. Carvalho, Hong Chen, et al.. Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS 2021 Competition and Demonstration Track, Dec 2021, On-line, United States. ⟨hal-03688638⟩
  • Sarah Hartley, Guillaume Bao, Marine Zagdoun, Sylvain Chevallier, Didier Lajoie, et al.. Un traitement innovant pour le syndrome des jambes sans repos pharmaco-résistant : la stimulation non invasive du nerf vague. Congrès du Sommeil 2021, Nov 2021, Lille, France. ⟨10.1016/j.msom.2022.01.017⟩. ⟨hal-04677589⟩
  • Roman Bresson, Johanne Cohen, Eyke Hüllermeier, Christophe Labreuche, Michele Sebag. On the Identifiability of Hierarchical Decision Models. 18th International Conference on Principles of Knowledge Representation and Reasoning (KR-2021), Nov 2021, Online, France. pp.151-162, ⟨10.24963/kr.2021/15⟩. ⟨hal-03453996⟩
  • Romain Egele, Prasanna Balaprakash, Venkatram Vishwanath, Isabelle Guyon, Zhengying Liu. AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data. SC '21: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Nov 2021, St. Louis, Missouri, United States. ⟨10.1145/3458817.3476203⟩. ⟨hal-02973288⟩
  • Alice Lacan, Isabelle Guyon. ML-CI: Machine Learning Confidence Intervals for Covid-19 forecasts. BayLearn - Machine Learning Symposium 2021, Oct 2021, San Francisco, United States. ⟨hal-03501101⟩
  • Victor Alfonso Naya, Guillaume Bied, Philippe Caillou, Bruno Crépon, Christophe Gaillac, et al.. Designing labor market recommender systems: the importance of job seeker preferences and competition. 4. IDSC of IZA Workshop: Matching Workers and Jobs Online - New Developments and Opportunities for Social Science and Practice, Oct 2021, Online, France. ⟨hal-03540319⟩
  • Adrien Pavao, Michael Vaccaro, Isabelle Guyon. Judging competitions and benchmarks: a candidate election approach. ESANN 2021 - 29th European Symposium on Artificial Neural Networks, Oct 2021, Bruges/Virtual, Belgium. ⟨hal-03367857v3⟩
  • Guillaume Bied, Elia Perennes, Victor Alfonso Naya, Philippe Caillou, Bruno Crépon, et al.. Congestion-Avoiding Job Recommendation with Optimal Transport. FEAST workshop ECML-PKDD 2021, Sep 2021, Bilbao, Spain. ⟨hal-03540316⟩
  • Wenzhuo Liu, Mouadh Yagoubi, Marc Schoenauer. Multi-resolution Graph Neural Networks for PDE Approximation. ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia. pp.151-163, ⟨10.1007/978-3-030-86365-4_13⟩. ⟨hal-03448278⟩
  • Manh Hung Nguyen, Nathan Grinsztajn, Isabelle Guyon, Lisheng Sun-Hosoya. MetaREVEAL: RL-based Meta-learning from Learning Curves. Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Sep 2021, Bilbao/Virtual, Spain. ⟨hal-03502358v2⟩
  • Georgios Zervakis, Emmanuel Vincent, Miguel Couceiro, Marc Schoenauer. On Refining BERT Contextualized Embeddings using Semantic Lexicons. ECML PKDD 2021 - Machine Learning with Symbolic Methods and Knowledge Graphs co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2021, Online, Spain. ⟨hal-03318571⟩
  • Omar Shrit, Michèle Sebag. I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterative Imitation Supervised Learning. EPIA 2021 - 20th EPIA Conference on Artificial Intelligence, Sep 2021, Virtual, Portugal. pp.418-432, ⟨10.1007/978-3-030-86230-5_33⟩. ⟨hal-03399149⟩
  • Ksenia Gasnikova, Philippe Caillou, Olivier Allais, Michèle Sebag. Towards causal modeling of nutritional outcomes. Causal Analysis Workshop Series (CAWS) 2021, Jul 2021, online, United States. pp.5-19. ⟨hal-03620867⟩
  • Aurélie Boisbunon, Carlo Fanara, Ingrid Grenet, Jonathan Daeden, Alexis Vighi, et al.. Zoetrope Genetic Programming for Regression. GECCO 2021, ACM, Jul 2021, Lille, France. pp.776-784, ⟨10.1145/3449639.3459349⟩. ⟨hal-03155694⟩
  • Johann Dreo, Arnaud Liefooghe, Sébastien Verel, Marc Schoenauer, Juan J. Merelo, et al.. Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics. GECCO 2021 - Genetic and Evolutionary Computation Conference, ACM Sigevo, Jul 2021, Lille / Virtual, France. pp.1522-1530, ⟨10.1145/3449726.3463276⟩. ⟨pasteur-03220556⟩
  • Thibaut Guégan, Michele Alessandro Bucci, Onofrio Semeraro, Laurent Cordier, Lionel Mathelin. Closed-loop control of complex systems using deep Reinforcement Learning. Euromech colloquium on Machine learning methods for turbulent separated flows, Jun 2021, Paris, France. ⟨hal-03451355⟩
  • Armand Lacombe, Saumya Jetley, Michèle Sebag. EXtremely PRIvate supervised Learning. Conférence d'APprentssage - CAP, Jun 2021, St-Etienne, France. ⟨hal-03620873⟩
  • Emmanuel Menier, Michele Alessandro Bucci, Mouadh Yagoubi, Marc Schoenauer. Complementary Deep - Reduced Order Model. Euromech colloquium on Machine learning methods for turbulent separated flows, Jun 2021, Paris, France. ⟨hal-03608578⟩
  • Julien Girard-Satabin, Aymeric Varasse, Guillaume Charpiat, Zakaria Chihani, Marc Schoenauer. Partitionnement en régions linéaires pour la vérification formelle de réseaux de neurones. Journées Francophones des Langages Applicatifs, Apr 2021, Saint Médard d’Excideuil, France. ⟨hal-03127853⟩
  • Omar Shrit, David Filliat, Michele Sebag. Iterative Learning for Model Reactive Control: Application to autonomous multi-agent control. ICARA 2021 - 7th International Conference on Automation, Robotics and Applications, Feb 2021, Prague, Czech Republic. ⟨10.1109/ICARA51699.2021.9376454⟩. ⟨hal-03133162⟩
  • Adrian El Baz, Isabelle Guyon, Zhengying Liu, Jan N van Rijn, Sebastien Treguer, et al.. Advances in MetaDL. AAAI 2021 challenge and workshop, Feb 2021, Virtual, France. ⟨hal-03550011⟩
  • Zhen Xu, Wei-Wei Tu, Isabelle Guyon. AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge. ECML PKDD 2021, 2021, Barcelona (virtual), Spain. ⟨hal-03299144v2⟩

Poster communications19 documents

  • Cyriaque Rousselot, Olivier Allais, Philippe Caillou, Julia Mink, Florian Yger. Assessing the Impact of Pesticide Exposure on Population Health Using Large-Scale Data Integration and Modelling. E4H Annual Forum 2024 - Engineering for Health Annual Forum, Nov 2024, Palaiseau (Ecole Polytechnique), France. ⟨hal-04991195⟩
  • Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat. Time and State Dependent Neural Delay Differential Equations. ML-DE@ECAI 2024 : Machine Learning Meets Differential Equations: From Theory to Applications, Sep 2024, Santiago de compostela, Galicia, Spain. ⟨hal-04794800⟩
  • Bruno Aristimunha, Thomas Moreau, Sylvain Chevallier, Raphael Y de Camargo, Marie-Constance Corsi. What is the best model for decoding neurophysiological signals? Depends on how you evaluate. CNS 2024 - 33rd Annual Computational Neuroscience Meeting, Jul 2024, Natal, Brazil. ⟨hal-04743845⟩
  • Igor Carrara, Bruno Aristimunha, Marie-Constance Corsi, Raphael Yokoingawa De Camargo, Sylvain Chevallier, et al.. Augmented SPDNet: Second-Order Neural Network for Motor Imagery-Based BCI. Soph.IA summit 2023, Nov 2023, Sophia Antipolis, France. ⟨hal-04308549⟩
  • Emmanuel Menier, Sebastian Kaltenbach, Mouadh Yagoubi, Marc Schoenauer, Koumoutsakos Petros. Interpretable reduced order modeling using neural autoencoders. MORTech 2023 – 6th International Workshop on Model Reduction Techniques, Nov 2023, Gif-sur Yvette, France. ⟨hal-04296372⟩
  • Maël Lefeuvre, Michael D. Martin, Flora Jay, Marie-Claude Marsolier, Alexis Corrochano, et al.. GRUPS-rs, a high-performance ancient DNA genetic relatedness estimation software relying on pedigree simulations. JOBIM 2023 - Journées Ouvertes en Biologie, Informatique et Mathématiques, Jun 2023, Multisite, France. ⟨hal-05242467⟩
  • Eva Boguslawski, Alessandro Leite, Marc Schoenauer, Matthieu Dussartre, Benjamin Donnot. Decentralized Partially Observable Markov Decision Process for Power Grid Management. Reinforcement Learning Summer School 2023, Jun 2023, Barcelone, Spain. . ⟨hal-04396121⟩
  • Eva Boguslawski, Alessandro Leite, Marc Schoenauer, Matthieu Dussartre, Benjamin Donnot. A Decision Support Assistant to Operate a Power Grids with Zonal Automatons. DTU PES Summer School 2023. Future Energy Systems: Advances in OR and AI., Jun 2023, Lingby, Denmark. . ⟨hal-04396136⟩
  • Maria Sayu Yamamoto, Sylvain Chevallier, Fabien Lotte. Effectiveness of cross-frequency phase-amplitude covariance as additional features for Riemannian BCIs. BCI 2023 - 10th International BCI Meeting Balancing Innovation and Translation, Jun 2023, Brussels, Belgium. ⟨10.3217/978-3-85125-962-9-179⟩. ⟨hal-04181391⟩
  • Romain Lloria, Florent Bouchard, Sylvain Chevallier, Frédéric Pascal. Blind separation with angular criteria. Journée du labo L2S, Jun 2023, Saint-Rémy-lès-Chevreuse, France. ⟨hal-05068005⟩
  • Igor Carrara, Bruno Aristimunha, Sylvain Chevallier, Marie-Constance Corsi, Théodore Papadopoulo. Holographic EEG: multi-view deep learning for BCI. Journée CORTICO 2023 - COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur, May 2023, Paris, France. . ⟨hal-04095900⟩
  • Rune Frateur, Sylvain Chevallier, Florian Yger, Marie-Constance Corsi. Dimensionality Reduction and Frequency Bin Optimization To Improve a Riemannian-based Classification Pipeline. CORTICO 2023 - Journées COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur, May 2023, Paris, France. . ⟨hal-04140107⟩
  • Emmanuel Goutierre, Christelle Bruni, Johanne Cohen, Hayg Guler, Michèle Sebag. Surrogate Model for Linear Accelerator: A fast Neural Network approximation of ThomX's simulator. IPAC 2023 - 14th International Particle Accelerator Conference, May 2023, Venice, Italy. JACoW Publishing, JACoW, IPAC2023, pp.4514-4517, 2023, ⟨10.18429/JACoW-IPAC2023-THPL039⟩. ⟨hal-04396183⟩
  • Arnaud Quelin, Jérémy Guez, Ferdinand Petit, Flora Jay, Frédéric Austerlitz. Inference of the Cultural Transmission of Reproductive Success from human genomic data: ABC and machine learning methods. Alphy/AIEM 2023 - Rencontres Alphy & AIEM, Jan 2023, Grenoble, France. ⟨hal-03960408⟩
  • Maël Lefeuvre, Michael D. Martin, Flora Jay, Marie-Claude Marsolier, Alexis Corrochano, et al.. GRUPS-rs: a high-performance ancient DNA genetic relatedness estimation software based on pedigree simulations. Bulletins et mémoires de la Société d’Anthropologie de Paris 35(S), Jan 2023, Paris, France. 35 (S), pp.30, 2023, ⟨10.4000/bmsap.11299⟩. ⟨hal-05242408⟩
  • Arnaud Quelin, Jérémy Guez, Ferdinand Petit, Flora Jay, Frederic Austerlitz. Inference of the Cultural Transmission of Reproductive Success from human genomic data: ABC and machine learning methods. Junior Conference on DataScience and Engeneering 2022, Sep 2022, Palaiseau, France. ⟨hal-04011855⟩
  • Isabelle Hoxha, Clark Bäker, Sylvain Chevallier, Stefan Glasauer, Michel Ange Amorim. Generating stimulus anticipation from stimulus and prediction history. BC 2022 - Bernstein Conference, Sep 2022, Berlin, Germany. ⟨10.12751/nncn.bc2022.049⟩. ⟨hal-03786876⟩
  • Louis Ollivier, Flora Jay, Fanny Pouyet. Impact of yeast cell cycle specificity on demography inference. JOBIM (Journées Ouvertes en Biologie, Informatique et Mathématiques ) 2022, Jul 2022, Rennes, France. ⟨hal-04393823⟩
  • Jérémy Guez, Guillaume Achaz, François Bienvenu, Jean Cury, Bruno Toupance, et al.. Understanding and inferring cultural transmission of reproductive success. Probabilistic Modeling in Genomics, Mar 2022, Oxford, United Kingdom. ⟨hal-04016758⟩

Proceedings1 document

  • François de Vieilleville, Stéphane May, Adrien Lagrange, A Dupuis, Rosa Ruiloba, et al.. Actes de la conférence CAID 2020. 2021. ⟨hal-03206297⟩

Special issue1 document

  • Paola Tubaro, Louise Ryan, Antonio A. Casilli, Alessio d'Angelo. Recent ethical challenges in social network analysis. Social Networks, 67, pp.1-76, 2021. ⟨hal-03331307⟩

Books1 document

  • Nayat Sanchez-Pi, Luis Marti, Julien Salomon, Jacques Sainte-Marie, Olivier Bernard, et al.. OcéanIA: AI, Data, and Models for Understanding the Ocean and Climate Change. pp.1-64, 2021. ⟨hal-03274323v2⟩

Book sections9 documents

  • François Cabestaing, Sylvain Chevallier. From signals to decisions in noninvasive neural technologies. Davide Valeriani; Theresa M. Vaughan. Neural Interfaces, Academic Press; Elsevier, pp.77-90, 2025, 978-0-443-24824-5. ⟨10.1016/C2023-0-51142-5⟩. ⟨hal-05266468⟩
  • Víctor Martín-Mayor, Juan Ruiz-Lorenzo, Beatriz Seoane, A. Peter Young. Numerical Simulations and Replica Symmetry Breaking. Spin Glass Theory and Far Beyond, WORLD SCIENTIFIC, pp.69-93, 2023, 978-981-12-7391-9. ⟨10.1142/9789811273926_0005⟩. ⟨hal-04341849⟩
  • Hugo Jair Escalante Balderas, Isabelle Guyon, Addison Howard, Walter Reade, Sebastien Treguer. Challenge design roadmap. AI Competitions and Benchmarks: The Science Behind the Contests, In press. ⟨hal-04333280v2⟩
  • Paola Tubaro. Social networks and resilience in emerging labor markets. E. Lazega, T.A.B. Snijders, R. Wittek. A Research Agenda for Social Networks and Social Resilience, Edward Elgar, pp.45-57, 2022, 978 1 80392 577 6. ⟨hal-03850444⟩
  • Francesco Arceri, François P. Landes, Ludovic Berthier, Giulio Biroli. Glasses and aging: A Statistical Mechanics Perspective. Encyclopedia of Complexity and Systems Science (Living Reference), 2022, ⟨10.1007/978-3-642-27737-5_248-2⟩. ⟨hal-02942375⟩
  • Adrian Alan Pol, Gianluca Cerminara, Cécile Germain, Maurizio Pierini. Data Quality Monitoring Anomaly Detection. Artificial Intelligence for High Energy Physics, World Scientific, 2022, ⟨10.1142/9789811234033_0004⟩. ⟨hal-03159873⟩
  • Paola Tubaro, Antonio A Casilli. Human Listeners and Virtual Assistants: Privacy and Labor Arbitrage in the Production of Smart Technologies. Mark Graham, Fabian Ferrari. Digital Work in the Planetary Market, The MIT Press, 2022, 9780262369824. ⟨10.7551/mitpress/13835.003.0014⟩. ⟨hal-03688430⟩
  • Erik Aurell, Jean Barbier, Aurélien Decelle, Roberto Mulet. The mighty force: statistical inference and high-dimensional statistics. Spin Glass Theory & Far Beyond - Replica Symmetry Breaking after 40 Years, World Scientific, In press, ⟨10.48550/arXiv.2205.00750⟩. ⟨hal-03795572⟩
  • Eugenio Lippiello, Giuseppe Petrillo, François P. Landes, Alberto Rosso. The genesis of aftershocks in spring slider models. Statistical Methods Modeleling of Seismogenesis, 1, Wiley, pp.131-151, 2021, 9781789450378. ⟨10.1002/9781119825050.ch5⟩. ⟨hal-04352840⟩

Scientific blog post1 document

  • Thomas Bäck, Pauline Bennet, Jacob de Nobel, Carola Doerr, Johann Dreo, et al.. Results from the Joint Nevergrad and IOHprofiler Open Optimization Competition. 2021. ⟨hal-04128653v1⟩

Preprints, Working Papers53 documents

  • Jad Yehya, Mansour Benbakoura, Cédric Allain, Benoît Malezieux, Matthieu Kowalski, et al.. RoseCDL: Robust and scalable convolutional dictionary learning for rare-event detection. 2025. ⟨hal-05250429⟩
  • Alexander Goldberg, Ihsan Ullah, Thanh Gia Hieu Khuong, Benedictus Kent Rachmat, Zhen Xu, et al.. Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS’24 Experiment. 2025. ⟨hal-05230379⟩
  • Guillaume Attuel, Matthieu Kowalski. Disentangling myth from reality: Nonlocality was not proven.. 2025. ⟨hal-04970178v7⟩
  • Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite, Nicolas Chesneau, Özgür Şimşek, et al.. Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption. 2025. ⟨hal-05066031v2⟩
  • Stéphane Rivaud, Louis Fournier, Thomas Pumir, Eugene Belilovsky, Michael Eickenberg, et al.. PETRA: Parallel End-to-end Training with Reversible Architectures. 2025. ⟨hal-04594647v2⟩
  • Nilo Schwencke, Cyril Furtlehner. ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning. 2024. ⟨hal-04849532⟩
  • Matthieu Kowalski, Benoît Malézieux, Thomas Moreau, Audrey Repetti. Analysis and synthesis denoisers for forward-backward plug-and-play algorithms. 2024. ⟨hal-04786802v3⟩
  • Dilek Koptekin, Ayça Aydoğan, Cansu Karamurat, N. Ezgi Altınışık, Kıvılcım Başak Vural, et al.. Out-of-Anatolia: cultural and genetic interactions during the Neolithic expansion in the Aegean. 2024. ⟨hal-04801125⟩
  • Burak Yelmen, Maris Alver, Estonian Biobank Research Team, Flora Jay, Lili Milani. Interpreting artificial neural networks to detect genome-wide association signals for complex traits. 2024. ⟨hal-04801114⟩
  • Antoine Szatkownik, Léo Planche, Maïwen Demeulle, Titouan Chambe, María Ávila-Arcos, et al.. Diffusion-based artificial genomes and their usefulness for local ancestry inference. 2024. ⟨hal-04801121⟩
  • Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Burak Yelmen, Flora Jay. Latent generative modeling of long genetic sequences with GANs. 2024. ⟨hal-04801130⟩
  • Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini, Onofrio Semeraro. Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows. 2024. ⟨hal-04794444⟩
  • Benoît Malézieux, Florent Michel, Thomas Moreau, Matthieu Kowalski. Where prior learning can and can't work in unsupervised inverse problems. 2024. ⟨hal-04782335⟩
  • Pierre Barbault, Matthieu Kowalski, Charles Soussen. Bernoulli and Gauss Take a Look at the MAP. 2024. ⟨hal-04782425⟩
  • Mariia Zameshina, Mathurin Videau, Alessandro Leite, Marc Schoenauer, Laurent Najman, et al.. Agnostic latent diversity enhancement in generative modeling. 2024. ⟨hal-04661473v2⟩
  • Mathurin Videau, Mariia Zameshina, Alessandro Leite, Laurent Najman, Marc Schoenauer, et al.. Evolutionary Retrofitting. 2024. ⟨hal-04733511⟩
  • Thibault Monsel, Emmanuel Menier, Lionel Mathelin, Onofrio Semeraro, Guillaume Charpiat. Neural DDEs with Learnable Delays for Partially Observed Dynamical Systems. 2024. ⟨hal-04715748⟩
  • Shuyu Dong, Bin Gao, Wen Huang, Kyle A. Gallivan. On the analysis of optimization with fixed-rank matrices: a quotient geometric view. 2024. ⟨hal-04710830⟩
  • Isabelle Hoxha, Sylvain Chevallier, Arnaud Delorme, Michel-Ange Amorim. EEG anticipatory activity depends on sensory modality. 2024. ⟨hal-04677650⟩
  • Bruno Aristimunha, Raphael de Camargo, Walter Pinaya, Sylvain Chevallier, Alexandre Gramfort, et al.. Evaluating the structure of cognitive tasks with transfer learning. 2024. ⟨hal-04677674⟩
  • Alice Lacan, Romain André, Michele Sebag, Blaise Hanczar. In Silico Generation of Gene Expression profiles using Diffusion Models. 2024. ⟨hal-05195584⟩
  • Romain Egele, Felix Mohr, Tom Viering, Prasanna Balaprakash. The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization. 2024. ⟨hal-04537565⟩
  • Sylvain Chevallier, Igor Carrara, Bruno Aristimunha, Pierre Guetschel, Sara Sedlar, et al.. The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark. 2024. ⟨hal-04537061⟩
  • Marion Ullmo, Nabila Aghnim, Aurélien Decelle, Miguel Aragon-Calvo. Predicting large scale cosmological structure evolution with GAN-based autoencoders. 2024. ⟨hal-04525380⟩
  • Matthieu Nastorg, Michele Alessandro Bucci, Thibault Faney, Jean-Marc Gratien, Guillaume Charpiat, et al.. An Implicit GNN Solver for Poisson-like problems. 2024. ⟨hal-03970501v3⟩
  • Mouadh Yagoubi, Milad Leyli-Abadi, David Danan, Jean-Patrick Brunet, Jocelyn Ahmed Mazari, et al.. ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design). 2024. ⟨hal-04944072⟩
  • Adrien Pavão. Hands-on tutorial on how to create your own challenge or benchmark. 2024. ⟨hal-04415747⟩
  • Wei-Wei Tu, Adrien Pavão. Special designs and competition protocols. 2024. ⟨hal-04416565⟩
  • Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, et al.. Optimizing Distributed Training on Frontier for Large Language Models. 2024. ⟨hal-04393799⟩
  • Edgar Jaber, Vincent Blot, Nicolas Brunel, Vincent Chabridon, Emmanuel Remy, et al.. Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees. 2024. ⟨hal-04389163⟩
  • Giovanni Catania, Aurélien Decelle, Beatriz Seoane. The Copycat Perceptron: Smashing Barriers Through Collective Learning. 2023. ⟨hal-04344030⟩
  • Aurélien Decelle, Cyril Furtlehner, Alfonso de Jesus Navas Gómez, Beatriz Seoane. Inferring effective couplings with Restricted Boltzmann Machines. 2023. ⟨hal-04342280⟩
  • Yu Guan, Shuyu Dong, Bin Gao, P. -A. Absil, François Glineur. Alternating minimization algorithms for graph regularized tensor completion. 2023. ⟨hal-04284961⟩
  • Shuyu Dong, Kento Uemura, Akito Fujii, Shuang Chang, Yusuke Koyanagi, et al.. Learning Large Causal Structures from Inverse Covariance Matrix via Matrix Decomposition. 2023. ⟨hal-03885791⟩
  • Fernando Villanea, David Peede, Eli Kaufman, Valeria Añorve-Garibay, Kelsey Witt, et al.. The MUC19 gene in Denisovans, Neanderthals, and Modern Humans: An Evolutionary History of Recurrent Introgression and Natural Selection. 2023. ⟨hal-04244022⟩
  • Birhanu Hailu Belay, Isabelle Guyon, Tadele Mengiste, Bezawork Tilahun, Marcus Liwicki, et al.. HHD-Ethiopic A Historical Handwritten Dataset for Ethiopic OCR with Baseline Models and Human-level Performance. 2023. ⟨hal-04223188⟩
  • Romain Egele, Tyler Chang, Yixuan Sun, Venkatram Vishwanath, Prasanna Balaprakash. Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives. 2023. ⟨hal-04219318⟩
  • Alexandre Quemy, Marc Schoenauer, Johann Dreo. MultiZenoTravel: a Tunable Benchmark for Multi-Objective Planning with Known Pareto Front. 2023. ⟨hal-04129698⟩
  • Thibault Monsel, Onofrio Semeraro, Lionel Mathelin, Guillaume Charpiat. Time and State Dependent Neural Delay Differential Equations. 2023. ⟨hal-04125875v3⟩
  • Audrey Poinsot, Alessandro Leite. A Guide for Practical Use of ADMG Causal Data Augmentation. 2023. ⟨hal-04250612⟩
  • Michele Quattromini, Michele Alessandro Bucci, Stefania Cherubini, Onofrio Semeraro. Operator learning of RANS equations: a Graph Neural Network closure model. 2023. ⟨hal-04290982⟩
  • Loris Felardos, Jérôme Hénin, Guillaume Charpiat. Designing losses for data-free training of normalizing flows on Boltzmann distributions. 2023. ⟨hal-03936982⟩
  • Manh Hung Nguyen, Lisheng Sun, Nathan Grinsztajn, Isabelle Guyon. Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round. 2022. ⟨hal-03725313⟩
  • Tamon Nakano, Michele Alessandro Bucci, Jean-Marc Gratien, Thibault Faney, Guillaume Charpiat. Machine learning model for gas-liquid interface reconstruction in CFD numerical simulations. 2022. ⟨hal-03721729⟩
  • Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, et al.. Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020. 2022. ⟨hal-03629994⟩
  • Antoine Fosset, Mohamed El-Mennaoui, Amine Rebei, Paul Calligaro, Elise Farge Di Maria, et al.. Docent: A content-based recommendation system to discover contemporary art. 2022. ⟨hal-04415857⟩
  • Michele Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen, Sergio Chibbaro, Lionel Mathelin. Leveraging the structure of dynamical systems for data-driven modeling. 2021. ⟨hal-03498482⟩
  • Julien Chiaroni, Sonja Zillner, Natalie Bertels, Patrick Bezombes, Yannick Bonhomme, et al.. Franco-German position paper on "Speeding up industrial AI and trustworthiness". 2021. ⟨hal-03488324⟩
  • Natalia Díaz-Rodríguez, Rūta Binkytė-Sadauskienė, Wafae Bakkali, Sannidhi Bookseller, Paola Tubaro, et al.. Questioning causality on sex, gender and COVID-19, and identifying bias in large-scale data-driven analyses: the Bias Priority Recommendations and Bias Catalog for Pandemics. 2021. ⟨hal-03228983⟩
  • Julien Girard-Satabin, Aymeric Varasse, Marc Schoenauer, Guillaume Charpiat, Zakaria Chihani. DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification. 2021. ⟨hal-03227439⟩
  • Victor Berger, Michele Sebag. Boltzmann Tuning of Generative Models. 2021. ⟨hal-03193948⟩
  • Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag. Distribution-Based Invariant Deep Networks for Learning Meta-Features. 2021. ⟨hal-03153200⟩
  • Léonard Blier, Corentin Tallec, Yann Ollivier. Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint. 2021. ⟨hal-03151901⟩

Reports4 documents

  • Sebastien Treguer, Marc Schoenauer. Lessons learned from TAILOR benchmarks/challenges. INRIA - team TAU. 2024. ⟨hal-04923991⟩
  • Adrien Pavao, Isabelle Guyon, Anne-Catherine Letournel, Xavier Baró, Hugo Escalante, et al.. CodaLab Competitions: An open source platform to organize scientific challenges. [Technical Report] Université Paris-Saclay, FRA. 2022. ⟨hal-03629462⟩
  • Odile Chagny, Antonio A. Casilli, Diouldé Chartier, Tristan d'Avezac, Fred Pailler, et al.. Les Nouveaux Intermédiaires du Travail B2B: Comparer les modèles d'affaires dans l'économie numérique collaborative. [Rapport de recherche] 27, DARES - Direction de l'animation de la recherche, des études et des statistiques du Ministère du travail, de l'emploi et de l'insertion. 2022. ⟨hal-03615806⟩
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Theses24 documents

  • Manon Verbockhaven. Spotting expressivity bottlenecks in neural networks and fixing them by optimal architecture growth. Neural and Evolutionary Computing [cs.NE]. Université Paris-Saclay, 2025. English. ⟨NNT : 2025UPASG022⟩. ⟨tel-05232707⟩
  • Thibault Monsel. Deep Learning for Partially Observed Dynamical Systems. Discrete Mathematics [cs.DM]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG113⟩. ⟨tel-04952358⟩
  • Francesco Pezzicoli. Statistical Physics - Machine Learning Interplay : from Addressing Class Imbalance with Replica Theory to Predicting Dynamical Heterogeneities with SE(3)-equivariant Graph Neural Networks. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG115⟩. ⟨tel-04910839⟩
  • Maria Sayu Yamamoto. Addressing the Large Variability of EEG Data with Riemannian Geometry : Toward Designing Reliable Brain-Computer Interfaces. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG098⟩. ⟨tel-04967163⟩
  • Apolline Mellot. Machine learning and domain adaptation for enhancing the measure of brain health with MEG and EEG signals. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG068⟩. ⟨tel-04906458⟩
  • Guillaume Bied. Designing Recommender Systems for the Labor Market. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG035⟩. ⟨tel-04740932⟩
  • Romain Egele. Optimization of Learning Workflows at Large Scale on High-Performance Computing Systems. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG025⟩. ⟨tel-04636586⟩
  • Matthieu Nastorg. Scalable GNN Solutions for CFD Simulations. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG020⟩. ⟨tel-04590477⟩
  • Armand Lacombe. Changes of representation for counter-factual inference. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG009⟩. ⟨tel-04759706⟩
  • Emmanuel Menier. Deep Learning for Reduced Order Modeling. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG004⟩. ⟨tel-04616516⟩
  • Haozhe Sun. Modularity in deep learning. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2023. English. ⟨NNT : 2023UPASG090⟩. ⟨tel-04418605⟩
  • Adrien Pavão. Methodology for Design and Analysis of Machine Learning Competitions. Machine Learning [cs.LG]. Université Paris-Saclay, 2023. English. ⟨NNT : 2023UPASG088⟩. ⟨tel-04401932v2⟩
  • Vincenzo Schimmenti. Temporal and spatial correlations in earthquake dynamics : physical modeling and data analysis. Statistical Mechanics [cond-mat.stat-mech]. Université Paris-Saclay, 2023. English. ⟨NNT : 2023UPASP159⟩. ⟨tel-04344778⟩
  • Wenzhuo Liu. Deep Graph Neural Networks for Numerical Simulation of PDEs. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2023. English. ⟨NNT : 2023UPASG032⟩. ⟨tel-04156859v2⟩
  • Herilalaina Rakotoarison. Some contributions to AutoML : hyper-parameter optimization and meta-learning. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASG044⟩. ⟨tel-03783610⟩
  • Léonard Blier. Sur certaines méthodes raisonnées pour l'apprentissage par renforcement profond. Apprentissage [cs.LG]. Université Paris-Saclay, 2022. Français. ⟨NNT : 2022UPASG040⟩. ⟨tel-03829500⟩
  • Théophile Sanchez. Reconstructing our past ˸ deep learning for population genetics. Neural and Evolutionary Computing [cs.NE]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASG032⟩. ⟨tel-03701132⟩
  • Balthazar Donon. Deep statistical solvers & power systems applications. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASG016⟩. ⟨tel-03624628⟩
  • Giancarlo Fissore. Generative modeling : statistical physics of Restricted Boltzmann Machines, learning with missing information and scalable training of Linear Flows. Disordered Systems and Neural Networks [cond-mat.dis-nn]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASG028⟩. ⟨tel-03710286⟩
  • Roman Bresson. Neural learning and validation of hierarchical multi-criteria decision aiding models with interacting criteria. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASG008⟩. ⟨tel-03596964⟩
  • Marion Ullmo. Emulation and prediction of cosmic web simulations through deep learning. Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]. Université Paris-Saclay, 2022. English. ⟨NNT : 2022UPASP012⟩. ⟨tel-03663099⟩
  • Zhengying Liu. Automated Deep Learning : Principles and Practice. Machine Learning [cs.LG]. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG094⟩. ⟨tel-03464519v2⟩
  • Julien Girard-Satabin. Verification and validation of Machine Learning techniques. Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG080⟩. ⟨tel-03547545⟩
  • Victor Berger. Modèles à Variables Latentes Profonds : des propriétés aux structures. Apprentissage [cs.LG]. Université Paris-Saclay, 2021. Français. ⟨NNT : 2021UPASG053⟩. ⟨tel-03528577⟩

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