Deep least-squares methods: An unsupervised learning-based numerical method for solving elliptic PDEs. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018; Xinyu Liu (J. Comput. Phys., 2020)

Least-Squares ReLU Neural Network (LSNN) Method For Scalar Nonlinear Hyperbolic Conservation Law. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018 (CoRR, 2021)

Finite Volume Least-Squares Neural Network (FV-LSNN) Method for Scalar Nonlinear Hyperbolic Conservation Laws. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018 (CoRR, 2021)

Least-squares ReLU neural network (LSNN) method for linear advection-reaction equation. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018 (J. Comput. Phys., 2021)

Adaptive two-layer ReLU neural network: I. Best least-squares approximation. - Min Liu 018; Zhiqiang Cai 001; Jingshuang Chen (Comput. Math. Appl., 2022)

Self-adaptive deep neural network: Numerical approximation to functions and PDEs. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018 (J. Comput. Phys., 2022)

Least-squares neural network (LSNN) method for scalar nonlinear hyperbolic conservation laws: Discrete divergence operator. - Zhiqiang Cai 001; Jingshuang Chen; Min Liu 018 (J. Comput. Appl. Math., 2023)