6 citations · 11 across the 6 of their papers we have counts for
Showing math.NAShow all
3 papers · 1 filter
math.NA2023★ 1 cited
Randomized Neural Networks with Petrov-Galerkin Methods for Solving Linear Elasticity Problems
Yong Shang, Fei Wang
We develop the Randomized Neural Networks with Petrov-Galerkin Methods (RNN-PG methods) to solve linear elasticity problems. RNN-PG methods use Petrov-Galerkin variational framewor…
math.NA2022★ 6 cited
Local Randomized Neural Networks with Discontinuous Galerkin Methods for Partial Differential Equations
Jingbo Sun, Suchuan Dong, Fei Wang
Randomized neural networks (RNN) are a variation of neural networks in which the hidden-layer parameters are fixed to randomly assigned values and the output-layer parameters are o…
math.NA2022★ 4 cited
Deep Petrov-Galerkin Method for Solving Partial Differential Equations
Yong Shang, Fei Wang, Jingbo Sun
Deep neural networks are powerful tools for approximating functions, and they are applied to successfully solve various problems in many fields. In this paper, we propose a neural…