4 citations · 5 across the 3 of their papers we have counts for
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math.NA2024
Overlapping Schwarz Preconditioners for Randomized Neural Networks with Domain Decomposition
Yong Shang, Alexander Heinlein, Siddhartha Mishra +1
Randomized neural networks (RaNNs), in which hidden layers remain fixed after random initialization, provide an efficient alternative for parameter optimization compared to fully p…
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★ 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…