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38 résultats
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triés par
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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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A principled learning strategy for chaotic dynamical systemsSIAM Mathematics of Data Science, Sep 2022, San diego, United States
Communication dans un congrès
hal-04406534v1
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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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Assessment of turbulent jet control possibilities by dynamical system analysisJournée de Dynamique des Fluides du Plateau de Saclay, Jan 2017, Orsay, France
Communication dans un congrès
hal-01633936v1
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Stability and optimal forcing analysis of a wind turbine wake: Comparison with PODRenewable Energy, 2022, 181, pp.765-785. ⟨10.1016/j.renene.2021.09.025⟩
Article dans une revue
hal-03498568v1
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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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Boundary layer transition induced by low-speed synthetic jetsPhysics of Fluids, 2022, 34, ⟨10.1063/5.0128798⟩
Article dans une revue
hal-03908267v1
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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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Full-order optimal compensators for flow control: the multiple inputs caseTheoretical and Computational Fluid Dynamics, 2018, 32 (3), pp.285-305. ⟨10.1007/s00162-018-0454-4⟩
Article dans une revue
hal-01841953v1
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End-to-end learning of dynamical systems with the Mori-Zwanzig formalismCSE 2023 - SIAM Computational Science and Engineering, Feb 2023, Amsterdam, Netherlands
Communication dans un congrès
hal-04406551v1
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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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Wavepackets in Subsonic Turbulent Jets: a Dynamical System AnalysisEUROMECH European Turbulence Conference, Aug 2017, Stockholm, Sweden
Communication dans un congrès
hal-01633939v1
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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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Leveraging the structure of dynamical systems for data-driven modeling2021
Pré-publication, Document de travail
hal-03498482v1
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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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Qualitative dynamics of wavepackets in turbulent jetsPhysical Review Fluids, 2017, 2, 30p. ⟨10.1103/PhysRevFluids.2.094605⟩
Article dans une revue
hal-01633922v1
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Resolvent-based modeling of coherent wave packets in a turbulent jetPhysical Review Fluids, 2019, 4 (6), ⟨10.1103/PhysRevFluids.4.063901⟩
Article dans une revue
hal-02151295v1
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Receptivity to synthetic jet actuation in boundary layer flowsAIAA Scitech 2020 Forum, Jan 2020, Orlando, FL, United States. ⟨10.2514/6.2020-0099⟩
Communication dans un congrès
hal-03087084v1
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Modeling of coherent structures in a turbulent jet as global linear instability wavepackets: Theory and experimentInternational Journal of Heat and Fluid Flow, 2016, 62, pp.24-32. ⟨10.1016/j.ijheatfluidflow.2016.10.010⟩
Article dans une revue
hal-02459554v1
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POD analysis of the recovery process in wind turbine wakesTORQUE 2020, Sep 2020, Delft, Italy
Poster de conférence
hal-03087099v1
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POD‐based analysis of a wind turbine wake under the influence of tower and nacelleWind Energy, 2020, ⟨10.1002/we.2592⟩
Article dans une revue
hal-03087079v1
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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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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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Reinforcement Learning for Control of Spatially Developing Distributed SystemsSIAM Computational Science and Engineering, Feb 2023, amsterdam, Netherlands
Communication dans un congrès
hal-04406548v1
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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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Input-output models for turbulent jetsEUROMECH Fluid Mechanics Conference, Sep 2018, Vienna, Austria
Communication dans un congrès
hal-02402676v1
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Nonlinear jet-flap interactions: a dynamical-systems analysis25th AIAA/CEAS Aeroacoustics Conference, AIAA, May 2019, Delft, Netherlands. ⟨10.2514/6.2019-2433⟩
Communication dans un congrès
hal-02378562v1
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