2 citations · 4 across the 4 of their papers we have counts for
5 papers
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…
Neural Networks Based on Power Method and Inverse Power Method for Solving Linear Eigenvalue Problems
Qihong Yang, Yangtao Deng, Yu Yang +2
In this article, we propose two kinds of neural networks inspired by power method and inverse power method to solve linear eigenvalue problems. These neural networks share similar…
A data-enabled physics-informed neural network with comprehensive numerical study on solving neutron diffusion eigenvalue problems
Yu Yang, Helin Gong, Shiquan Zhang +4
We present a data-enabled physics-informed neural network (DEPINN) with comprehensive numerical study for solving industrial scale neutron diffusion eigenvalue problems (NDEPs). In…
An Optimal Embedded Discontinuous Galerkin Method for Second-Order Elliptic Problems
Xiao Zhang, Xiaoping Xie, Shiquan Zhang
The embedded discontinuous Galerkin (EDG) method by Cockburn et al. [SIAM J. Numer. Anal., 2009, 47(4), 2686-2707] is obtained from the hybridizable discontinuous Galerkin method b…
A new smoothness result for Caputo-type fractional ordinary differential equations
Binjie Li, Xiaoping Xie, Shiquan Zhang
We present a new smoothness result for Caputo-type fractional ordinary differential equations, which reveals that, subtracting a non-smooth function that can be obtained by the inf…