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Architectural Strategies for the optimization of Physics-Informed Neural
  Networks

Architectural Strategies for the optimization of Physics-Informed Neural Networks

5 February 2024
Hemanth Saratchandran
Shin-Fang Chng
Simon Lucey
    AI4CE
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Papers citing "Architectural Strategies for the optimization of Physics-Informed Neural Networks"

3 / 3 papers shown
Title
Probing optimisation in physics-informed neural networks
Probing optimisation in physics-informed neural networks
Nayara Fonseca
V. Guidetti
Will Trojak
26
1
0
27 Mar 2023
On the eigenvector bias of Fourier feature networks: From regression to
  solving multi-scale PDEs with physics-informed neural networks
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
126
435
0
18 Dec 2020
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
616
0
13 Mar 2020
1