14 citations · 17 across the 4 of their papers we have counts for
4 papers
HANN: Homotopy auxiliary neural network for solving nonlinear algebraic equations
Ling-Zhe Zai, Lei-Lei Guo, Zhi-Yong Zhang
Solving nonlinear algebraic equations is a fundamental but challenging problem in scientific computations and also has many applications in system engineering. Though traditional i…
Invariant deep neural networks under the finite group for solving partial differential equations
Zhi-Yong Zhang, Jie-Ying Li, Lei-Lei Guo
Utilizing physics-informed neural networks (PINN) to solve partial differential equations (PDEs) becomes a hot issue and also shows its great powers, but still suffers from the dil…
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…
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),…