Variational training of neural network approximations of solution maps for physical models

7 May 2019

Papers citing "Variational training of neural network approximations of solution maps for physical models"

9 / 9 papers shown

Title
On the choice of the non-trainable internal weights in random feature maps Pinak Mandal Georg Gottwald Nicholas Cranch TPM 40 1 0 07 Aug 2024
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 62 386 0 06 Nov 2021
Cell-average based neural network method for hyperbolic and parabolic partial differential equations Changxin Qiu Jue Yan 16 10 0 02 Jul 2021
Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization Zhongshu Xu Yingzhou Li Xiuyuan Cheng 21 8 0 09 Dec 2019
Solving Optical Tomography with Deep Learning Yuwei Fan Lexing Ying 19 15 0 10 Oct 2019
Meta-learning Pseudo-differential Operators with Deep Neural Networks Jordi Feliu-Fabà Yuwei Fan Lexing Ying 22 39 0 16 Jun 2019
Solving Electrical Impedance Tomography with Deep Learning Yuwei Fan Lexing Ying 28 100 0 06 Jun 2019
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning Yufei Wang Ziju Shen Zichao Long Bin Dong AI4CE PINN 13 40 0 27 May 2019
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018