27 citations · 40 across the 5 of their papers we have counts for
5 papers
Computing Multi-Eigenpairs of High-Dimensional Eigenvalue Problems Using Tensor Neural Networks
Yifan Wang, Hehi Xie
In this paper, we propose a type of tensor-neural-network-based machine learning method to compute multi-eigenpairs of high dimensional eigenvalue problems without Monte-Carlo proc…
NAS-PINN: Neural architecture search-guided physics-informed neural network for solving PDEs
Yifan Wang, Linlin Zhong
Physics-informed neural network (PINN) has been a prevalent framework for solving PDEs since proposed. By incorporating the physical information into the neural network through los…
Accelerating physics-informed neural network based 1D arc simulation by meta learning
Linlin Zhong, Bingyu Wu, Yifan Wang
Physics-Informed Neural Networks (PINNs) have a wide range of applications as an alternative to traditional numerical methods in plasma simulation. However, in some specific cases…
Solving Schrödinger Equation Using Tensor Neural Network
Yangfei Liao, Zhongshuo Lin, Jianghao Liu +5
In this paper, we introduce a novel approach to solve the many-body Schrodinger equation by the tensor neural network. Based on the tensor product structure, we can do the direct n…
Tensor Neural Network and Its Numerical Integration
Yifan Wang, Pengzhan Jin, Hehu Xie
In this paper, we introduce a type of tensor neural network. For the first time, we propose its numerical integration scheme and prove the computational complexity to be the polyno…