3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Symmetry group based domain decomposition to enhance physics-informed neural networks for solving partial differential equations
Ye Liu, Jie-Ying Li, Li-Sheng Zhang +2
Domain decomposition provides an effective way to tackle the dilemma of physics-informed neural networks (PINN) which struggle to accurately and efficiently solve partial different…
cs.LG2022★ 3 cited
Enforcing continuous symmetries in physics-informed neural network for solving forward and inverse problems of partial differential equations
Zhi-Yong Zhang, Hui Zhang, Li-Sheng Zhang +1
As a typical application of deep learning, physics-informed neural network (PINN) {has been} successfully used to find numerical solutions of partial differential equations (PDEs),…