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Preconditioning for Physics-Informed Neural Networks

Preconditioning for Physics-Informed Neural Networks

1 February 2024
Songming Liu
Chang Su
J. Yao
Zhongkai Hao
Hang Su
Youjia Wu
Jun Zhu
    AI4CE
    PINN
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Papers citing "Preconditioning for Physics-Informed Neural Networks"

3 / 3 papers shown
Title
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
Nilo Schwencke
Cyril Furtlehner
64
1
0
14 Dec 2024
Physics-informed neural networks with hard constraints for inverse
  design
Physics-informed neural networks with hard constraints for inverse design
Lu Lu
R. Pestourie
Wenjie Yao
Zhicheng Wang
F. Verdugo
Steven G. Johnson
PINN
39
493
0
09 Feb 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
170
756
0
13 Mar 2020
1