Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees).

Gaël Poëtte

Paul Novello Gaël Poëtte David Lugato Simon Peluchon Pietro Marco Congedo Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). 112700 2024 February 498 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2023.112700 db/journals/jcphy/jcphy498.html#NovelloPLPC24

Bilel Bensaid Gaël Poëtte Rodolphe Turpault An Abstract Lyapunov Control Optimizer: Local Stabilization and Global Convergence. 2024 abs/2407.01019 CoRR https://doi.org/10.48550/arXiv.2407.01019 db/journals/corr/corr2407.html#abs-2407-01019 streams/journals/corr

Gaël Poëtte Multigroup-like MC resolution of generalised Polynomial Chaos reduced models of the uncertain linear Boltzmann equation (+discussion on hybrid intrusive/non-intrusive uncertainty propagation). 111825 2023 February 474 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2022.111825 db/journals/jcphy/jcphy474.html#Poette23

Paul Novello Gaël Poëtte David Lugato Pietro Marco Congedo Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. 45 2023 February 94 J. Sci. Comput. 3 https://doi.org/10.1007/s10915-022-02083-4 db/journals/jscic/jscic94.html#NovelloPLC23

Bilel Bensaid Gaël Poëtte Rodolphe Turpault Deterministic Neural Networks Optimization from a Continuous and Energy Point of View. 14 2023 July 96 J. Sci. Comput. 1 https://doi.org/10.1007/s10915-023-02215-4 db/journals/jscic/jscic96.html#BensaidPT23

Gaël Poëtte Efficient uncertainty propagation for photonics: Combining Implicit Semi-analog Monte Carlo (ISMC) and Monte Carlo generalised Polynomial Chaos (MC-gPC). 110807 2022 450 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2021.110807 db/journals/jcphy/jcphy450.html#Poette22

Gaël Poëtte Emeric Brun Efficient uncertain <i>k</i><sub>eff</sub> computations with the Monte Carlo resolution of generalised Polynomial Chaos based reduced models. 111007 2022 456 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2022.111007 db/journals/jcphy/jcphy456.html#PoetteB22

Paul Novello Gaël Poëtte David Lugato Pietro Marco Congedo Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning. 2022 abs/2207.06216 CoRR https://doi.org/10.48550/arXiv.2207.06216 db/journals/corr/corr2207.html#abs-2207-06216

Paul Novello Gaël Poëtte David Lugato Simon Peluchon Pietro Marco Congedo Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees). 2022 abs/2209.13434 CoRR https://doi.org/10.48550/arXiv.2209.13434 db/journals/corr/corr2209.html#abs-2209-13434

Paul Novello Gaël Poëtte David Lugato Pietro Marco Congedo Variance Based Samples Weighting for Supervised Deep Learning. 2021 abs/2101.07561 CoRR https://arxiv.org/abs/2101.07561 db/journals/corr/corr2101.html#abs-2101-07561

Gaël Poëtte Xavier Valentin A new Implicit Monte-Carlo scheme for photonics (without teleportation error and without tilts). 109405 2020 412 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2020.109405 db/journals/jcphy/jcphy412.html#PoetteV20

Gaël Poëtte Spectral convergence of the generalized Polynomial Chaos reduced model obtained from the uncertain linear Boltzmann equation. 24-45 2020 177 Math. Comput. Simul. https://doi.org/10.1016/j.matcom.2020.04.009 db/journals/mcs/mcs177.html#Poette20

Gaël Poëtte Contribution to the Mathematical and numerical Analysis of uncertain Systems of conservation Laws and of the linear and nonlinear Boltzmann equation. (Contribution a l'analyse Mathematique et numerique des systemes de lois de conservation incertains et de l'equation de Boltzmann Lineaire et non-Lineaire). 2019 University of Bordeaux, France https://tel.archives-ouvertes.fr/tel-02288678

Gaël Poëtte A gPC-intrusive Monte-Carlo scheme for the resolution of the uncertain linear Boltzmann equation. 135-162 2019 385 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2019.01.052 https://www.wikidata.org/entity/Q128319973 db/journals/jcphy/jcphy385.html#Poette19

Adrien Bernede Gaël Poëtte An Unsplit Monte-Carlo solver for the resolution of the linear Boltzmann equation coupled to (stiff) Bateman equations. 211-241 2018 354 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2017.10.027 db/journals/jcphy/jcphy354.html#BernedeP18

Gaël Poëtte Alexandre Birolleau Didier Lucor Iterative Polynomial Approximation Adapting to Arbitrary Probability Distribution. 1559-1584 2015 53 SIAM J. Numer. Anal. 3 https://doi.org/10.1137/140963170 db/journals/siamnum/siamnum53.html#PoetteBL15

Bruno Després Gaël Poëtte Didier Lucor Robust Uncertainty Propagation in Systems of Conservation Laws with the Entropy Closure Method. 105-149 2013 Uncertainty Quantification in Computational Fluid Dynamics https://doi.org/10.1007/978-3-319-00885-1_3 series/lncse/92 db/series/lncse/lncse92.html#DespresPL13

Gaël Poëtte Didier Lucor Non intrusive iterative stochastic spectral representation with application to compressible gas dynamics. 3587-3609 2012 231 J. Comput. Phys. 9 https://doi.org/10.1016/j.jcp.2011.12.038 db/journals/jcphy/jcphy231.html#PoetteL12

Gaël Poëtte Bruno Després Didier Lucor Uncertainty quantification for systems of conservation laws. 2443-2467 2009 228 J. Comput. Phys. 7 https://doi.org/10.1016/j.jcp.2008.12.018 db/journals/jcphy/jcphy228.html#PoetteDL09

Bilel Bensaid Adrien Bernede Alexandre Birolleau Emeric Brun Pietro Marco Congedo Bruno Després Didier Lucor David Lugato Paul Novello Simon Peluchon Rodolphe Turpault Xavier Valentin