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cs.LG2025
Deep Parallel Spectral Neural Operators for Solving Partial Differential Equations with Enhanced Low-Frequency Learning Capability
Qinglong Ma, Peizhi Zhao, Sen Wang +1
Designing universal artificial intelligence (AI) solver for partial differential equations (PDEs) is an open-ended problem and a significant challenge in science and engineering. C…
cs.LG2024
ASPINN: An asymptotic strategy for solving singularly perturbed differential equations
Sen Wang, Peizhi Zhao, Tao Song
Solving Singularly Perturbed Differential Equations (SPDEs) presents challenges due to the rapid change of their solutions at the boundary layer. In this manuscript, We propose Asy…
cs.LG2024
General-Kindred Physics-Informed Neural Network to the Solutions of Singularly Perturbed Differential Equations
Sen Wang, Peizhi Zhao, Qinglong Ma +1
Physics-Informed Neural Networks (PINNs) have become a promising research direction in the field of solving Partial Differential Equations (PDEs). Dealing with singular perturbatio…