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Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks
v1v2 (latest)

Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks

28 June 2024
Wenqian Chen
Amanda A. Howard
P. Stinis
    AI4CE
ArXiv (abs)PDFHTMLGithub (6★)

Papers citing "Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks"

2 / 2 papers shown
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
Sizhuang He
Ananyae Kumar Bhartari
Bowen Li
P. Perdikaris
PINN
508
45
0
02 Feb 2025
SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks
SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks
Ashish S. Nair
Amanda A. Howard
P. Stinis
245
20
0
09 Nov 2024
1
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