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	Pour les 58 documents Envoyer sur ORCID RSS ATOM Exporter BibTeX XML-TEI CSV RTF EndNote PDF HTML Export avancé	Page : Page précédente 1 2 Page suivante	triés par Pertinence Auteur A→Z Auteur Z→A Titre A→Z Titre Z→A Date de publication croissante Date de publication décroissante Date de dépôt croissante Date de dépôt décroissante

		Curriculum learning for data-driven modeling of dynamical systems Onofrio Semeraro , Michele Alessandro Bucci , Alexandre Allauzen , Sergio Chibbaro , Lionel Mathelin Dynamics Days Europe 2023, Sep 2023, Napoli, Italy Communication dans un congrès hal-04407784v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		CD-ROM -- Complementary Deep - Reduced Order Model Emmanuel Menier , Michele Alessandro Bucci , Mouadh Yagoubi , Marc Schoenauer , Lionel Mathelin IUTAM Symposium on Data-driven modeling and optimization in fluid mechanics 2022, Jun 2022, Aarhus, Denmark Communication dans un congrès hal-04405482v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		CD-ROM: Complemented Deep-Reduced Order Model Emmanuel Menier , Michele Alessandro Bucci , Mouadh Yagoubi , Lionel Mathelin , Marc Schoenauer MORTech 2023 - 6th International Workshop on Model Order Reduction, Nov 2023, Saclay, France Communication dans un congrès hal-04406567v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Stochastic data assimilation of the random shallow water model loads with uncertain experimental measurements L. Mathelin , Christophe Desceliers , M.Yussuf Hussaini Computational Mechanics, 2011, 47 (6), pp.603-616 Article dans une revue hal-00750190v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		New approaches to learn low-rank models of dynamical systems from streaming data Alex Gorodetsky , Lionel Mathelin International Conference on Uncertainty Quantification in Computational Science and Engineering, Jun 2019, Heraklion (Crete Island), Greece Communication dans un congrès hal-04405368v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Optimal control for shear flows using Reinforcement Learning Onofrio Semeraro , Remy Hosseinkhan Boucher , Amine Saibi , Michele Alessandro Bucci , Lionel Mathelin IUTAM Symposium on Data-driven modeling and optimization in fluid mechanics, Jun 2022, Aarhus, Denmark Communication dans un congrès hal-03854596v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Data-driven estimation of a turbulent flow from wall sensors Lionel Mathelin , Srikanth Derebail Muralidhar , Bérengère Podvin US-Japan Workshop on bridging Fluid Mechanics and Data Science, Mar 2018, Tokyo (Japan), Japan Communication dans un congrès hal-04406584v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Latent Dirichlet Allocation: a new machine learning tool to evaluate CMIP6 climate models atmospheric circulation Nemo Malhomme , Davide Faranda , Bérengère Podvin , Lionel Mathelin European Meteorological Society annual meeting, Sep 2022, Bonn, Germany Communication dans un congrès hal-04406521v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Global optimization with Gaussian process and application to drag reduction with vortex generators Thomas Rouillon , Fabien Harambat , Christian Tenaud , Lionel Mathelin World Congress on Global Optimization in Engineering & Science, Jan 2011, Chania, Greece Communication dans un congrès hal-01629397v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Control of chaotic systems by deep reinforcement learning Michele Alessandro Bucci , Onofrio Semeraro , Alexandre Allauzen , Guillaume Wisniewski , Laurent Cordier , et al. Proceedings 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	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		A statistical learning strategy for closed-loop control of fluid flows Florimond Guéniat , Lionel Mathelin , M.Yussuf Hussaini 2016 Pré-publication, Document de travail hal-01271248v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Leveraging the structure of dynamical systems for data-driven modeling Michele Alessandro Bucci , Onofrio Semeraro , Alexandre Allauzen , Sergio Chibbaro , Lionel Mathelin 2021 Pré-publication, Document de travail hal-03498482v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Closed-loop control of complex systems using deep Reinforcement Learning Thibaut Guégan , Michele Alessandro Bucci , Onofrio Semeraro , Laurent Cordier , Lionel Mathelin Euromech colloquium on Machine learning methods for turbulent separated flows, Jun 2021, Paris, France Communication dans un congrès hal-03451355v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Closed-loop optimal control for shear flows using reinforcement learning Onofrio Semeraro , Michele Alessandro Bucci , Lionel Mathelin 73rd Annual APS/DFD Meeting, Nov 2020, Chicago, United States Communication dans un congrès hal-03101416v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Global optimization of vortex generator parameters for drag reduction of ground vehicles Thomas Rouillon , Fabien Harambat , Lionel Mathelin , Christian Tenaud CFD & OPTIMIZATION, An ECCOMAS Thematic Conference, Jan 2011, Antalaya, Turkey Communication dans un congrès hal-01629396v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Modélisation par termes source de générateurs de vortex pour le contrôle d'écoulement : validations expérimentales et optimisations Thomas Rouillon , Fabien Harambat , Christian Tenaud , Lionel Mathelin , A. Queuille Congrès Français de Mécanique, Jan 2011, Besançon, France Communication dans un congrès hal-01629399v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Apprentissage d’un modèle dynamique chaotique par un LSTM Michele Alessandro Bucci , Alexandre Allauzen , Laurent Cordier , Lionel Mathelin , Onofrio Semeraro , et al. Conférence sur l’Apprentissage automatique (CAp), Jul 2019, Toulouse, France Communication dans un congrès hal-02412444v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		When deep learning meets ergodic theory Michele Alessandro Bucci , Onofrio Semeraro , Sergio Chibbaro , Alexandre Allauzen , Lionel Mathelin 73rd Annual APS/DFD Meeting, Nov 2020, Chicago / Virtual, United States Communication dans un congrès hal-03101431v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		End-to-end learning of dynamical systems with the Mori-Zwanzig formalism Thibault Monsel , Lionel Mathelin , Onofrio Semeraro , Guillaume Charpiat CSE 2023 - SIAM Computational Science and Engineering, Feb 2023, Amsterdam, Netherlands Communication dans un congrès hal-04406551v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Observable Dictionary Learning for High-Dimensional Statistical Inference Lionel Mathelin , Kévin Kasper , Hisham Abou-Kandil Archives of Computational Methods in Engineering, 2018, 25 (1), pp.103 - 120. ⟨10.1007/s11831-017-9219-2⟩ Article dans une revue hal-01726821v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		An overview of aircraft vibration environment prediction using machine learning Stéphane Février , Stéphane Nachar , Lionel Mathelin , Frédéric Giordano , Bérengère Podvin Computational Challenges and Emerging Tools Workshop, Apr 2023, Cambridge, United Kingdom Poster de conférence hal-04185152v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Control of chaotic systems by deep reinforcement learning Michele Alessandro Bucci , Onofrio Semeraro , Alexandre Allauzen , Guillaume Wisniewski , Laurent Cordier , et al. Dynamical Methods in Data-based Exploration of Complex Systems, international workshop, Oct 2019, Dresden, Germany Poster de conférence hal-03087089v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Toward control of weakly observed nonlinear dynamical systems using reinforcement learning Charles Pivot , Alex Gorodetsky , Lionel Mathelin , Laurent Cordier SIAM UQ18 (SIAM Conference on Uncertainty Quantification 2018), SIAM Society for Industrial and Applied Mathematics, Apr 2018, Garden Grove, CA, United States Communication dans un congrès hal-04405140v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Thermal large eddy simulations for high temperature solar receivers Adrien Toutant , Martin David , Françoise Bataille , Yanis Zatout , Lionel Mathelin , et al. 17th International Heat Transfer Conference, Aug 2023, Cape Town, South Africa Poster de conférence hal-04240801v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Unsupervised identification of motifs in turbulent channel flow using Latent Dirichlet Allocation Mohamed Frihat , Némo Malhomme , Bérengère Podvin , Lionel Mathelin , Yann Fraigneau , et al. Euromech colloquium on Machine learning methods for turbulent separated flows, Jun 2021, Paris, France Communication dans un congrès hal-03451341v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Spatio-temporal proper orthogonal decomposition of turbulent channel flow Srikanth Derebail Muralidhar , Bérengère Podvin , Lionel Mathelin , Yann Fraigneau Journal of Fluid Mechanics, 2019, 864, pp.614-639. ⟨10.1017/jfm.2019.48⟩ Article dans une revue hal-02170063v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Toward the prediction of chaotic systems for the Reinforcement Learning of turbulent flows Michele Alessandro Bucci , Alex Gorodetsky , Onofrio Semeraro , Alexandre Allauzen , Sergio Chibbaro , et al. International Workshop on Dynamical Methods in Data-based Exploration of Complex Systems, Max Planck Institute, Oct 2019, Dresden, Germany Communication dans un congrès hal-04405377v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Exploration strategies for control of chaotic dynamical systems using reinforcement learning Rémy Hosseinkhan Boucher , Amine Saibi , Michele Alessandro Bucci , Onofrio Semeraro , Lionel Mathelin European Drag Reduction and Flow Control Meeting - EDRFCM 2022, Sep 2022, Paris, France Communication dans un congrès hal-03854602v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Shallow neural networks for fluid flow reconstruction with limited sensors N. Benjamin Erichson , Lionel Mathelin , Zhewei Yao , Steven Brunton , Michael Mahoney , et al. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020, 476 (2238), pp.20200097. ⟨10.1098/rspa.2020.0097⟩ Article dans une revue hal-03059296v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Data-Driven Prediction of Aircraft Vibration Environment During Unsteady Flight Dynamics Stéphane Février , Stéphane Nachar , Lionel Mathelin , Frédéric Giordano , Bérengère Podvin 1st Annual Aerospace Structures, Structural Dynamics, and Materials Conference (SSDM), ASME, Jun 2023, San Diego (California), United States Communication dans un congrès hal-04185012v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More

Filtrer vos résultats

Curriculum learning for data-driven modeling of dynamical systems

CD-ROM -- Complementary Deep - Reduced Order Model

CD-ROM: Complemented Deep-Reduced Order Model

Stochastic data assimilation of the random shallow water model loads with uncertain experimental measurements

New approaches to learn low-rank models of dynamical systems from streaming data

Optimal control for shear flows using Reinforcement Learning

Data-driven estimation of a turbulent flow from wall sensors

Latent Dirichlet Allocation: a new machine learning tool to evaluate CMIP6 climate models atmospheric circulation

Global optimization with Gaussian process and application to drag reduction with vortex generators

Control of chaotic systems by deep reinforcement learning

A statistical learning strategy for closed-loop control of fluid flows

Leveraging the structure of dynamical systems for data-driven modeling

Closed-loop control of complex systems using deep Reinforcement Learning

Closed-loop optimal control for shear flows using reinforcement learning

Global optimization of vortex generator parameters for drag reduction of ground vehicles

Modélisation par termes source de générateurs de vortex pour le contrôle d'écoulement : validations expérimentales et optimisations

Apprentissage d’un modèle dynamique chaotique par un LSTM

When deep learning meets ergodic theory

End-to-end learning of dynamical systems with the Mori-Zwanzig formalism

Observable Dictionary Learning for High-Dimensional Statistical Inference

An overview of aircraft vibration environment prediction using machine learning

Control of chaotic systems by deep reinforcement learning

Toward control of weakly observed nonlinear dynamical systems using reinforcement learning

Thermal large eddy simulations for high temperature solar receivers

Unsupervised identification of motifs in turbulent channel flow using Latent Dirichlet Allocation

Spatio-temporal proper orthogonal decomposition of turbulent channel flow

Toward the prediction of chaotic systems for the Reinforcement Learning of turbulent flows

Exploration strategies for control of chaotic dynamical systems using reinforcement learning

Shallow neural networks for fluid flow reconstruction with limited sensors

Data-Driven Prediction of Aircraft Vibration Environment During Unsteady Flight Dynamics