2 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
A Novel Fourier Feature Network for Solving Partial Differential Equations
Qihong Yang, Zhijie Su, Yangtao Deng +1
Building on the foundation of single-hidden-layer neural networks, Fourier Feature Networks (FENs) are proposed, which incorporate Fourier features using , , or a combi…
A Novel Tensor Product-Based Neural Network for Solving Partial Differential Equations
Qihong Yang, Yangtao Deng, Qiaolin He +1
This paper presents the Tensor Product Network (TPNet), a novel neural architecture for efficient and accurate function approximation and PDE solving. The core of the proposal invo…
Multi-Scale Separable Fourier Neural Networks for Solving High-Frequency PDEs
Qihong Yang, Qiaolin He
Solving high-frequency partial differential equations (PDEs) with neural networks is notoriously difficult due to the spectral bias of conventional architectures. We propose the Mu…
On the uncertainty analysis of the data-enabled physics-informed neural network for solving neutron diffusion eigenvalue problem
Yu Yang, Helin Gong, Qihong Yang +3
In practical engineering experiments, the data obtained through detectors are inevitably noisy. For the already proposed data-enabled physics-informed neural network (DEPINN) \cite…