Search Results

• Bi-Orthogonal fPINN: A Physics-Informed Neural Network Method for Solving Time-Dependent Stochastic Fractional PDEs

  Lei Ma, Rongxin Li, Fanhai Zeng, Ling Guo, George Em Karniadakis

  2023-11-08

  31843 2797 Pages:1133-1176

• A Variational Neural Network Approach for Glacier Modelling with Nonlinear Rheology

  Tiangang Cui, Zhongjian Wang, Zhiwen Zhang

  2023-11-08

  30842 2583 Pages:934-954

• An Augmented Lagrangian Deep Learning Method for Variational Problems with Essential Boundary Conditions

  Jianguo Huang, Haoqin Wang, Tao Zhou

  2022-03-03

  50575 3314 Pages:966-986

• Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions

  Yulei Liao, Pingbing Ming

  2021-03-24

  53300 3485 Pages:1365-1384

• Convergence Rate Analysis for Deep Ritz Method

  Chenguang Duan, Yuling Jiao, Yanming Lai, Dingwei Li, Xiliang Lu, Jerry Zhijian Yang

  2022-03-30

  58970 3389 Pages:1020-1048

• Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations

  Ameya D. Jagtap, George Em Karniadakis

  2020-11-18

  149394 6595 Pages:2002-2041

• VPVnet: A Velocity-Pressure-Vorticity Neural Network Method for the Stokes’ Equations under Reduced Regularity

  Yujie Liu, Chao Yang

  2022-03-03

  45524 3235 Pages:739-770

• DL-PDE: Deep-Learning Based Data-Driven Discovery of Partial Differential Equations from Discrete and Noisy Data

  Hao Xu, Haibin Chang, Dongxiao Zhang

  2021-01-13

  55176 3525 Pages:698-728

• Deep Unfitted Nitsche Method for Elliptic Interface Problems

  Hailong Guo, Xu Yang

  2022-03-30

  52625 3284 Pages:1162-1179