Preface: machine-learning approaches for computational mechanics Z. LiGuohui HuG. E. Karniadakis EditorialNotes 03 July 2023 Pages: 1035 - 1038
Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics W. WuM. DanekerL. Lu OriginalPaper Open access 03 July 2023 Pages: 1039 - 1068
Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving partial differential equations with sharp solutions Zhiping MaoXuhui Meng OriginalPaper Open access 03 July 2023 Pages: 1069 - 1084
Peri-Net-Pro: the neural processes with quantified uncertainty for crack patterns M. KimG. Lin OriginalPaper Open access 16 June 2023 Pages: 1085 - 1100
An artificial viscosity augmented physics-informed neural network for incompressible flow Yichuan HeZhicheng WangDawei Tang OriginalPaper Open access 22 June 2023 Pages: 1101 - 1110
Variational inference in neural functional prior using normalizing flows: application to differential equation and operator learning problems Xuhui Meng OriginalPaper Open access 03 July 2023 Pages: 1111 - 1124
Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures H. Q. YouX. XuJ. Foster OriginalPaper Open access 03 July 2023 Pages: 1125 - 1150
Deep convolutional Ritz method: parametric PDE surrogates without labeled data J. N. FuhgA. KarmarkarN. Bouklas OriginalPaper Open access 03 July 2023 Pages: 1151 - 1174
A dive into spectral inference networks: improved algorithms for self-supervised learning of continuous spectral representations J. WuS. F. WangP. Perdikaris OriginalPaper Open access 03 July 2023 Pages: 1199 - 1224
