1 citations · 2 across the 2 of their papers we have counts for
2 papers
math.NA2023★ 1 cited
Solving a class of multi-scale elliptic PDEs by means of Fourier-based mixed physics informed neural networks
Xi'an Li, Jinran Wu, You-Gan Wang +2
Deep neural networks have garnered widespread attention due to their simplicity and flexibility in the fields of engineering and scientific calculation. In this study, we probe int…
math.DS2023★ 1 cited
Physical informed neural networks with soft and hard boundary constraints for solving advection-diffusion equations using Fourier expansions
Xi'an Li, Jiaxin Deng, Jinran Wu +3
Deep learning methods have gained considerable interest in the numerical solution of various partial differential equations (PDEs). One particular focus is physics-informed neural…