Fabien Casenave

Orcid: 0000-0002-8810-9128

According to our database1, Fabien Casenave authored at least 21 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Manifold Learning - Model Reduction in Engineering
Springer Briefs in Computer Science, Springer, ISBN: 978-3-031-52766-1, 2024

2023
BasicTools: a numerical simulation toolbox.
J. Open Source Softw., June, 2023

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability.
CoRR, 2023

A priori compression of convolutional neural networks for wave simulators.
CoRR, 2023

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases.
J. Comput. Phys., 2022

An updated Gappy-POD to capture non-parameterized geometrical variation in fluid dynamics problems.
Adv. Model. Simul. Eng. Sci., 2022

2021
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN.
CoRR, 2021

Optimal piecewise linear data compression for solutions of parametrized partial differential equations.
CoRR, 2021

Uncertainty quantification for industrial design using dictionaries of reduced order models.
CoRR, 2021

Physics-informed cluster analysis and a priori efficiency criterion for the construction of local reduced-order bases.
CoRR, 2021

Data augmentation and feature selection for automatic model recommendation in computational physics.
CoRR, 2021

2020
Model order reduction assisted by deep neural networks (ROM-net).
Adv. Model. Simul. Eng. Sci., 2020

A nonintrusive reduced order model for nonlinear transient thermal problems with nonparametrized variability.
Adv. Model. Simul. Eng. Sci., 2020

Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability.
Proceedings of the Intelligent Computing, 2020

Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows.
Proceedings of the Intelligent Computing, 2020

2016
Variants of the Empirical Interpolation Method: Symmetric formulation, choice of norms and rectangular extension.
Appl. Math. Lett., 2016

2015
Boundary element and finite element coupling for aeroacoustics simulations.
J. Comput. Phys., 2015

A nonintrusive reduced basis method applied to aeroacoustic simulations.
Adv. Comput. Math., 2015

2014
Coupled BEM-FEM for the convected Helmholtz equation with non-uniform flow in a bounded domain.
J. Comput. Phys., 2014

An Empirical Interpolation based Fast Summation Method for translation invariant kernels.
CoRR, 2014


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