Fabien Casenave

27 papers A* 1Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Learning large scale industrial physics simulations. CoRR Fabien Casenave
2025	J	`jnl`	NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis. CoRR Mouadh Yagoubi, David Danan, Milad Leyli-Abadi, Jocelyn Ahmed Mazari, Jean-Patrick Brunet, Abbas Kabalan, Fabien Casenave, Yuxin Ma, Giovanni Catalani, Jean Fesquet, Jacob Helwig, Xuan Zhang, Haiyang Yu, Xavier Bertrand, Frederic Tost, Michael Bauerheim, Joseph Morlier, Shuiwang Ji
2025	J	`jnl`	O-MMGP: Optimal Mesh Morphing Gaussian Process Regression for Solving PDEs with non-Parametric Geometric Variations. CoRR Abbas Kabalan, Fabien Casenave, Felipe Bordeu, Virginie Ehrlacher
2025	J	`jnl`	Physics-Learning AI Datamodel (PLAID) datasets: a collection of physics simulations for machine learning. CoRR Fabien Casenave, Xavier Roynard, Brian Staber, William Piat, Michele Alessandro Bucci, Nissrine Akkari, Abbas Kabalan, Xuan Minh Vuong Nguyen, Luca Saverio, Raphaël Carpintero Perez, Anthony Kalaydjian, Samy Fouché, Thierry Gonon, Ghassan Najjar, Emmanuel Menier, Matthieu Nastorg, Giovanni Catalani, Christian Rey
2024	J	`jnl`	An elasticity-based mesh morphing technique with application to reduced-order modeling. CoRR Abbas Kabalan, Fabien Casenave, Felipe Bordeu, Virginie Ehrlacher, Alexandre Ern
2024	—	`book`	Manifold Learning - Model Reduction in Engineering David Ryckelynck, Fabien Casenave, Nissrine Akkari
2023	J	`jnl`	A priori compression of convolutional neural networks for wave simulators. CoRR Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2023	J	`jnl`	A priori compression of convolutional neural networks for wave simulators. Eng. Appl. Artif. Intell. Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2023	J	`jnl`	BasicTools: a numerical simulation toolbox. J. Open Source Softw. Felipe Bordeu, Fabien Casenave, Julien Cortial
2023	J	`jnl`	MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability. CoRR Fabien Casenave, Brian Staber, Xavier Roynard
2023	A*	`conf`	MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability. NeurIPS Fabien Casenave, Brian Staber, Xavier Roynard
2022	J	`jnl`	An updated Gappy-POD to capture non-parameterized geometrical variation in fluid dynamics problems. Adv. Model. Simul. Eng. Sci. Nissrine Akkari, Fabien Casenave, David Ryckelynck, Christian Rey
2022	J	`jnl`	Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. J. Comput. Phys. Thomas Daniel, Fabien Casenave, Nissrine Akkari, Ali Ketata, David Ryckelynck
2021	J	`jnl`	Data augmentation and feature selection for automatic model recommendation in computational physics. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2021	J	`jnl`	Optimal piecewise linear data compression for solutions of parametrized partial differential equations. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2021	J	`jnl`	Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases. CoRR Thomas Daniel, Ali Ketata, Fabien Casenave, David Ryckelynck
2021	J	`jnl`	Uncertainty quantification for industrial design using dictionaries of reduced order models. CoRR Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck, Christian Rey
2021	J	`jnl`	Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN. CoRR Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
2020	J	`jnl`	A nonintrusive reduced order model for nonlinear transient thermal problems with nonparametrized variability. Adv. Model. Simul. Eng. Sci. Fabien Casenave, Asven Gariah, Christian Rey, Frédéric Feyel
2020	—	`conf`	Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows. SAI (2) Nissrine Akkari, Fabien Casenave, Marc-Eric Perrin, David Ryckelynck
2020	J	`jnl`	Model order reduction assisted by deep neural networks (ROM-net). Adv. Model. Simul. Eng. Sci. Thomas Daniel, Fabien Casenave, Nissrine Akkari, David Ryckelynck
2020	—	`conf`	Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability. SAI (2) Fabien Casenave, Nissrine Akkari, David Ryckelynck
2016	J	`jnl`	Variants of the Empirical Interpolation Method: Symmetric formulation, choice of norms and rectangular extension. Appl. Math. Lett. Fabien Casenave, Alexandre Ern, Tony Lelièvre
2015	J	`jnl`	A nonintrusive reduced basis method applied to aeroacoustic simulations. Adv. Comput. Math. Fabien Casenave, Alexandre Ern, Tony Lelièvre
2015	J	`jnl`	Boundary element and finite element coupling for aeroacoustics simulations. J. Comput. Phys. Nolwenn Balin, Fabien Casenave, François Dubois, Eric Duceau, Stefan Duprey, Isabelle Terrasse
2014	J	`jnl`	An Empirical Interpolation based Fast Summation Method for translation invariant kernels. CoRR Fabien Casenave
2014	J	`jnl`	Coupled BEM-FEM for the convected Helmholtz equation with non-uniform flow in a bounded domain. J. Comput. Phys. Fabien Casenave, Alexandre Ern, Guillaume Sylvand