Model order reduction assisted by deep neural networks (ROM-net) T Daniel, F Casenave, N Akkari, D Ryckelynck Advanced Modeling and Simulation in Engineering Sciences 7, 1-27, 2020 | 91 | 2020 |

A nonintrusive reduced basis method applied to aeroacoustic simulations F Casenave, A Ern, T Lelievre Advances in Computational Mathematics 41 (5), 961-986, 2015 | 60 | 2015 |

Coupled BEM–FEM for the convected Helmholtz equation with non-uniform flow in a bounded domain F Casenave, A Ern, G Sylvand Journal of Computational Physics 257, 627-644, 2014 | 49 | 2014 |

A nonintrusive distributed reduced‐order modeling framework for nonlinear structural mechanics—Application to elastoviscoplastic computations F Casenave, N Akkari, F Bordeu, C Rey, D Ryckelynck International journal for numerical methods in engineering 121 (1), 32-53, 2020 | 41 | 2020 |

Accurate and online-efficient evaluation of the *a posteriori *error bound in the reduced basis methodF Casenave, A Ern, T Lelièvre ESAIM: Mathematical Modelling and Numerical Analysis 48 (1), 207-229, 2014 | 41 | 2014 |

Boundary element and finite element coupling for aeroacoustics simulations N Balin, F Casenave, F Dubois, E Duceau, S Duprey, I Terrasse Journal of Computational Physics 294, 274-296, 2015 | 31 | 2015 |

Direct measurement of evapotranspiration from a forest using a superconducting gravimeter M Van Camp, O de Viron, G Pajot‐Métivier, F Casenave, A Watlet, ... Geophysical Research Letters 43 (19), 10,225-10,231, 2016 | 30 | 2016 |

Time stable reduced order modeling by an enhanced reduced order basis of the turbulent and incompressible 3D Navier–Stokes equations N Akkari, F Casenave, V Moureau Mathematical and computational applications 24 (2), 45, 2019 | 29 | 2019 |

Accurate a posteriori error evaluation in the reduced basis method F Casenave Comptes Rendus Mathematique 350 (9-10), 539-542, 2012 | 26 | 2012 |

Fast computation of general forward gravitation problems F Casenave, L Métivier, G Pajot-Métivier, I Panet Journal of Geodesy 90, 655-675, 2016 | 24 | 2016 |

Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases T Daniel, F Casenave, N Akkari, A Ketata, D Ryckelynck Journal of Computational Physics 458, 111120, 2022 | 18 | 2022 |

Data augmentation and feature selection for automatic model recommendation in computational physics T Daniel, F Casenave, N Akkari, D Ryckelynck Mathematical and Computational Applications 26 (1), 17, 2021 | 14 | 2021 |

Méthodes de réduction de modèles appliquées à des problèmes d'aéroacoustique résolus par équations intégrales F Casenave Paris Est, 2013 | 13* | 2013 |

An error indicator-based adaptive reduced order model for nonlinear structural mechanics—application to high-pressure turbine blades F Casenave, N Akkari Mathematical and computational applications 24 (2), 41, 2019 | 12 | 2019 |

A catching-up algorithm for multibody dynamics with impacts and dry friction A Charles, F Casenave, C Glocker Computer Methods in Applied Mechanics and Engineering 334, 208-237, 2018 | 12 | 2018 |

A bayesian nonlinear reduced order modeling using variational autoencoders N Akkari, F Casenave, E Hachem, D Ryckelynck Fluids 7 (10), 334, 2022 | 11 | 2022 |

A nonintrusive reduced order model for nonlinear transient thermal problems with nonparametrized variability F Casenave, A Gariah, C Rey, F Feyel Advanced Modeling and Simulation in Engineering Sciences 7, 1-19, 2020 | 11 | 2020 |

Uncertainty quantification for industrial numerical simulation using dictionaries of reduced order models T Daniel, F Casenave, N Akkari, D Ryckelynck, C Rey Mechanics & Industry 23, 3, 2022 | 6 | 2022 |

Data-targeted prior distribution for variational autoencoder N Akkari, F Casenave, T Daniel, D Ryckelynck Fluids 6 (10), 343, 2021 | 6 | 2021 |

Deep convolutional generative adversarial networks applied to 2D incompressible and unsteady fluid flows N Akkari, F Casenave, ME Perrin, D Ryckelynck Science and Information Conference, 264-276, 2020 | 6 | 2020 |