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32 résultats
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triés par
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Control of chaotic systems by deep reinforcement learningDynamical Methods in Data-based Exploration of Complex Systems, international workshop, Oct 2019, Dresden, Germany
Poster de conférence
hal-03087089v1
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Enhancing Data-Assimilation in CFD using Graph Neural Networks37th Conference on Neural Information Processing Systems (Neurips 2023), Dec 2023, New Orleans (LA), United States
Poster de conférence
hal-04407779v1
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Control of chaotic systems by deep reinforcement learningProceedings of the Royal Society of London. Series A, Mathematical and physical sciences, In press, 475 (2231), pp.1-20. ⟨10.1098/rspa.2019.0351⟩
Article dans une revue
hal-02406677v1
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Curriculum learning for data-driven modeling of dynamical systemsDynamics Days Europe 2023, Sep 2023, Napoli, Italy
Communication dans un congrès
hal-04407784v1
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CD-ROM -- Complementary Deep - Reduced Order ModelIUTAM Symposium on Data-driven modeling and optimization in fluid mechanics 2022, Jun 2022, Aarhus, Denmark
Communication dans un congrès
hal-04405482v1
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CD-ROM: Complemented Deep-Reduced Order ModelMORTech 2023 - 6th International Workshop on Model Order Reduction, Nov 2023, Saclay, France
Communication dans un congrès
hal-04406567v1
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Operator learning of RANS equations: a Graph Neural Network closure model2023
Pré-publication, Document de travail
hal-04290982v1
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Toward the prediction of chaotic systems for the Reinforcement Learning of turbulent flowsInternational Workshop on Dynamical Methods in Data-based Exploration of Complex Systems, Max Planck Institute, Oct 2019, Dresden, Germany
Communication dans un congrès
hal-04405377v1
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Operator learning of RANS equations: a Graph Neural Network closure modelThe mathematical and statistical foundation of future data-driven engineering -- Computational Challenges and Emerging Tools, Apr 2023, Cambridge, United Kingdom
Poster de conférence
hal-04407775v1
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Numerical and experimental analysis of combustion in microchannels with controlled temperatureChemical Engineering Science: X, 2019, 4, pp.100034. ⟨10.1016/j.cesx.2019.100034⟩
Article dans une revue
hal-02317402v1
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Curriculum learning for data-driven modeling of dynamical systemsEuropean Physical Journal E: Soft matter and biological physics, 2023, 46 (3), pp.12. ⟨10.1140/epje/s10189-023-00269-8⟩
Article dans une revue
hal-04291002v1
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Machine learning model for gas-liquid interface reconstruction in CFD numerical simulations2022
Pré-publication, Document de travail
hal-03721729v1
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Multi-Level GNN Preconditioner for Solving Large Scale Problems2024
Pré-publication, Document de travail
hal-04447099v1
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An Implicit GNN Solver for Poisson-like problems2024
Pré-publication, Document de travail
hal-03970501v3
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CD-ROM: Complementary Deep-Reduced Order ModelComputer Methods in Applied Mechanics and Engineering, 2023, 410
Article dans une revue
hal-03846122v1
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Closed-loop control of complex systems using deep Reinforcement LearningEuromech colloquium on Machine learning methods for turbulent separated flows, Jun 2021, Paris, France
Communication dans un congrès
hal-03451355v1
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Closed-loop optimal control for shear flows using reinforcement learning73rd Annual APS/DFD Meeting, Nov 2020, Chicago, United States
Communication dans un congrès
hal-03101416v1
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Roughness-induced transition by quasi-resonance of a varicose global modeJournal of Fluid Mechanics, 2017, 836, pp.167-191. ⟨10.1017/jfm.2017.791⟩
Article dans une revue
hal-02444299v1
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Apprentissage d’un modèle dynamique chaotique par un LSTMConférence sur l’Apprentissage automatique (CAp), Jul 2019, Toulouse, France
Communication dans un congrès
hal-02412444v1
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When deep learning meets ergodic theory73rd Annual APS/DFD Meeting, Nov 2020, Chicago / Virtual, United States
Communication dans un congrès
hal-03101431v1
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A synthetic forcing to trigger laminar-turbulent transition in parallel wall bounded flows via receptivityJournal of Computational Physics, 2019, 393, pp.92-116. ⟨10.1016/j.jcp.2019.04.011⟩
Article dans une revue
hal-02462856v1
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Global stability analysis of 3D micro-combustion modelCombustion and Flame, 2016, 167, pp.132-148. ⟨10.1016/j.combustflame.2016.02.018⟩
Article dans une revue
hal-02454411v1
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Subcritical and supercritical dynamics of incompressible flow over miniaturized roughness elementsFluids mechanics [physics.class-ph]. Ecole nationale supérieure d'arts et métiers - ENSAM, 2017. English. ⟨NNT : 2017ENAM0053⟩
Thèse
tel-01881371v1
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Control of chaotic systems by Deep Reinforcement Learning2019
Pré-publication, Document de travail
hal-02411475v1
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Control of a chaotic dynamical system with a Deep Reinforcement Learning approach90th GAMM Annual Meeting, Feb 2019, Vienna, Austria
Communication dans un congrès
hal-02411514v1
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Continuous Methods : Adaptively intrusive reduced order model closureICML 2022 - Workshop Continuous time methods for machine learning, Jul 2022, Baltimore, United States
Communication dans un congrès
hal-03879332v1
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Exploration Strategies in Reinforcement Learning Maximum Entropy optimisation applied to chaotic PDE controlSIAM Computational Science and Engineering, Feb 2023, Amsterdam, Netherlands
Communication dans un congrès
hal-04406558v1
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Time-Stepping and Krylov Method for large scale instability problemsComputational modelling of bifurcations and instabilities in fluid dynamics, Springer, pp.33-73, 2018, 9783319914947. ⟨10.1007/978-3-319-91494-7_2⟩
Chapitre d'ouvrage
hal-02445571v1
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Control-oriented model learning with a recurrent neural network71st Annual APS/DFD Meeting, Nov 2018, Atlanta, United States
Communication dans un congrès
hal-02411907v1
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DS-GPS : A Deep Statistical Graph Poisson SolverNeurIPS 2022 - Machine Learning and the Physical Sciences, workshop, Dec 2022, New-Orleans, United States
Communication dans un congrès
hal-03864015v1
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