Communication dans un congrès
Matière Condensée
Affichage des résultats 1 à 12 sur 36 au total
Matière Condensée : 1 à 12 sur 36 au total
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Thèse
Loris Felardos. Data-free Generation of Molecular Configurations with Normalizing Flows. Machine Learning [cs.LG]. Université Grenoble Alpes [2020-..], 2022. English. ⟨NNT : 2022GRALM026⟩. ⟨tel-04010123⟩
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Article dans une revue
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⟩
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Communication dans un congrès
Marko Pavlov, Anne Migan-Dubois, Vincent Bourdin, Michel Pons, Jordi Badosa, et al.. Experimental and Numerical Study of the Influence of String Mismatch on the Yield of PV Modules Augmented By Static Planar Reflectors. 42nd IEEE Photovoltaic Specialists Conference (PVSC), Jun 2015, New Orleans, United States. ⟨10.1109/pvsc.2015.7356176⟩. ⟨hal-01239571⟩
Année de publication
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Communication dans un congrès
Marko Pavlov, Anne Migan-Dubois, Vincent Bourdin, Michel Pons. Experiment and modelling of photovoltaic modules under solar flux augmented by planar reflectors in a Paris suburb climate. 28th international conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2015), J.-P. Bédécarrats Ed., Pub. Pau Univ. France, Jun 2015, Pau, France. ⟨hal-01239572⟩
Année de publication
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Poster de conférence
Marko Pavlov, Anne Migan-Dubois, Vincent Bourdin, Michel Pons, Jordi Badosa, et al.. A study of the impact of climate on the optimal geometry of a LCPV system. European Photovoltaic Solar Energy Conference (Eu-PVSEC 2015), Sep 2015, Hamburg, Germany. , 5BV.1.33, 2015. ⟨hal-01239562⟩
Année de publication
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Communication dans un congrès
Anne Migan-Dubois, Thomas Mambrini, Jordi Badosa, Martial Haeffelin, Joaquim Nassar, et al.. Multi-technology photovoltaic module test bench on the SIRTA meteorological and climate observatory. AUST international conference in technology (AUSTECH 2015), African University of Science and Technology, Oct 2015, Abuja, Nigeria. ⟨hal-01239557⟩
Année de publication
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Pré-publication, Document de travail
Loris Felardos, Jérôme Hénin, Guillaume Charpiat. Designing losses for data-free training of normalizing flows on Boltzmann distributions. 2023. ⟨hal-03936982⟩
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Article dans une revue
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⟩
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Article dans une revue
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⟩
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Article dans une revue
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⟩
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Chapitre d'ouvrage
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⟩