Search Results for author: Jingshuang Chen

Found 5 papers, 1 papers with code

Least-Squares Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Laws: Discrete Divergence Operator

no code implementations21 Oct 2021 Zhiqiang Cai, Jingshuang Chen, Min Liu

A least-squares neural network (LSNN) method was introduced for solving scalar linear and nonlinear hyperbolic conservation laws (HCLs) in [7, 6].

Numerical Integration

Self-adaptive deep neural network: Numerical approximation to functions and PDEs

no code implementations7 Sep 2021 Zhiqiang Cai, Jingshuang Chen, Min Liu

Designing an optimal deep neural network for a given task is important and challenging in many machine learning applications.

Least-Squares ReLU Neural Network (LSNN) Method For Linear Advection-Reaction Equation

no code implementations25 May 2021 Zhiqiang Cai, Jingshuang Chen, Min Liu

This paper studies least-squares ReLU neural network method for solving the linear advection-reaction problem with discontinuous solution.

Least-Squares ReLU Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Law

no code implementations25 May 2021 Zhiqiang Cai, Jingshuang Chen, Min Liu

We introduced the least-squares ReLU neural network (LSNN) method for solving the linear advection-reaction problem with discontinuous solution and showed that the method outperforms mesh-based numerical methods in terms of the number of degrees of freedom.

Numerical Integration

Deep least-squares methods: an unsupervised learning-based numerical method for solving elliptic PDEs

1 code implementation5 Nov 2019 Zhiqiang Cai, Jingshuang Chen, Min Liu, Xinyu Liu

This paper studies an unsupervised deep learning-based numerical approach for solving partial differential equations (PDEs).

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