1 citations · 2 across the 4 of their papers we have counts for
4 papers
Normalized Fourier-induced PINN method for solving the wave propagation equation in a non-unitized domain over an extended time range
Jichao Ma, Dandan Liu, Jinran Wu +1
Physics-Informed Neural Networks (PINNs) have gained significant attention for their simplicity and flexibility in engineering and scientific computing. In this study, we introduce…
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise
Yilong Hou, Xi'an Li, Jinran Wu +1
Bayesian Physics Informed Neural Networks (BPINN) have attracted considerable attention for inferring the system states and physical parameters of differential equations according…
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…
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…