Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations

21 March 2023

Papers citing "Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations"

5 / 5 papers shown

Title
Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling Adrienne M. Propp Daniel M. Tartakovsky AI4CE 26 2 0 16 Oct 2024
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification Nuojin Cheng Osman Asif Malik Subhayan De Stephen Becker Alireza Doostan 8 9 0 25 May 2023
Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion S. Basir Inanc Senocak PINN AI4CE 34 68 0 30 Sep 2021
Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities Mengwu Guo Andrea Manzoni Maurice Amendt Paolo Conti J. Hesthaven 68 95 0 26 Feb 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sifan Wang Hanwen Wang P. Perdikaris 131 438 0 18 Dec 2020