MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability
Paper • 2305.12871 • Published
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NionioÂ
authored 2
papers 8 months ago
fabiencasenaveÂ
authored 3
papers over 1 year ago
Physics-Learning AI Datamodel (PLAID) datasets: a collection of physics simulations for machine learning
Paper • 2505.02974 • Published
O-MMGP: Optimal Mesh Morphing Gaussian Process Regression for Solving PDEs with non-Parametric Geometric Variations
Paper • 2502.11632 • Published
Learning large scale industrial physics simulations
Paper • 2502.08295 • Published
fabiencasenaveÂ
authored 15
papers about 2 years ago
An elasticity-based mesh morphing technique with application to reduced-order modeling
Paper • 2407.02433 • Published
A Nonintrusive Distributed Reduced Order Modeling Framework for nonlinear structural mechanics -- application to elastoviscoplastic computations
Paper • 1812.07228 • Published
An error indicator-based adaptive reduced order model for nonlinear structural mechanics -- application to high-pressure turbine blades
Paper • 1904.09123 • Published
Nonintrusive approximation of parametrized limits of matrix power algorithms -- application to matrix inverses and log-determinants
Paper • 1710.02488 • Published
Variants of the Empirical Interpolation Method: symmetric formulation, choice of norms and rectangular extension
Paper • 1508.05330 • Published
A Fast Summation Method for translation invariant kernels
Paper • 1408.0210 • Published
Boundary Element and Finite Element Coupling for Aeroacoustics Simulations
Paper • 1402.2439 • Published
A nonintrusive Reduced Basis Method applied to aeroacoustic simulations
Paper • 1401.3684 • Published
Accurate and efficient evaluation of the a posteriori error estimator in the reduced basis method
Paper • 1212.0970 • Published
Coupled BEM-FEM for the convected Helmholtz equation with non-uniform flow in a bounded domain
Paper • 1303.6923 • Published
A nonintrusive method to approximate linear systems with nonlinear parameter dependence
Paper • 1307.4330 • Published
Accurate a posteriori error evaluation in the reduced basis method
Paper • 1205.6051 • Published
A priori compression of convolutional neural networks for wave simulators
Paper • 2304.04964 • Published
Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN
Paper • 2110.13680 • Published
Optimal piecewise linear data compression for solutions of parametrized partial differential equations
Paper • 2108.12291 • Published