A cell functional minimization scheme for parabolic problem. - Li Yin; Jiming Wu; Yanzhong Yao (J. Comput. Phys., 2010)

A Conservative Domain Decomposition Procedure for Nonlinear Diffusion Problems on Arbitrary Quadrilateral Grids. - Guangwei Yuan; Yanzhong Yao; Li Yin (SIAM J. Sci. Comput., 2011)

A cell functional minimization scheme for domain decomposition method on non-orthogonal and non-matching meshes. - Li Yin; Jiming Wu; Yanzhong Yao (Numerische Mathematik, 2014)

An efficient parallel iteration algorithm for nonlinear diffusion equations with time extrapolation techniques and the Jacobi explicit scheme. - Shuai Miao; Yanzhong Yao; Guixia Lv (J. Comput. Phys., 2021)

An interpolation-free cell-centered discretization of the heterogeneous and anisotropic diffusion problems on polygonal meshes. - Shuai Miao; Jiming Wu; Yanzhong Yao (Comput. Math. Appl., 2023)

A deep learning method for multi-material diffusion problems based on physics-informed neural networks. - Yanzhong Yao; Jiawei Guo; Tongxiang Gu (CoRR, 2023)

A deep learning framework for multi-scale models based on physics-informed neural networks. - Yong Wang; Yanzhong Yao; Jiawei Guo; Zhiming Gao (CoRR, 2023)

Pre-training strategy for solving evolution equations based on physics-informed neural networks. - Jiawei Guo; Yanzhong Yao; Han Wang; Tongxiang Gu (J. Comput. Phys., 2023)

A practical PINN framework for multi-scale problems with multi-magnitude loss terms. - Yong Wang; Yanzhong Yao; Jiawei Guo; Zhiming Gao (J. Comput. Phys., 2024)

2D 3T PINNs for solving 2-D 3-T heat conduction equations based on physics-informed neural networks. - Xiaojun Lei; Tongxiang Gu; Xiaowen Xu; Hengbin An; Yanzhong Yao (Comput. Phys. Commun., 2025)

An extrapolation-driven network architecture for physics-informed deep learning. - Yong Wang; Yanzhong Yao; Zhiming Gao (Neural Networks, 2025)

Hard constraint learning approaches with trainable influence functions for evolutionary equations. - Yushi Zhang; Shuai Su; Yong Wang; Yanzhong Yao (CoRR, 2025)