Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs

5 February 2022

Papers citing "Deep-HyROMnet: A deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs"

6 / 6 papers shown

Title
Neural empirical interpolation method for nonlinear model reduction Max Hirsch F. Pichi J. Hesthaven 37 1 0 05 Jun 2024
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 42 4 0 04 Apr 2024
Deep Learning-based surrogate models for parametrized PDEs: handling geometric variability through graph neural networks N. R. Franco S. Fresca Filippo Tombari Andrea Manzoni AI4CE 29 16 0 03 Aug 2023
A graph convolutional autoencoder approach to model order reduction for parametrized PDEs F. Pichi B. Moya J. Hesthaven AI4CE 38 52 0 15 May 2023
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 23 34 0 06 Dec 2022
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning Ben Adcock Juan M. Cardenas N. Dexter 33 8 0 25 Aug 2022