- Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts. Machine learning moment closure models for the radiative transfer equation I: Directly learning a gradient based closure. J. Comput. Physics, 453:110941, 2022.
- Sifan Wang, Xinling Yu, Paris Perdikaris. When and why PINNs fail to train: A neural tangent kernel perspective. J. Comput. Physics, 449:110768, 2022.
- Yu Gao, Hongyu Liu, Xianchao Wang, Kai Zhang. On an artificial neural network for inverse scattering problems. J. Comput. Physics, 448:110771, 2022.
- Lijing Yang, Milad Rakhsha, Wei Hu, Dan Negrut. A consistent multiphase flow model with a generalized particle shifting scheme resolved via incompressible SPH. J. Comput. Physics, 458:111079, 2022.
- Lei Yuan, Yi Qing Ni, Xiang-Yun Deng, Shuo Hao. A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations. J. Comput. Physics, 462:111260, 2022.
- Evan S. Gawlik, François Gay-Balmaz. B = 0. J. Comput. Physics, 450:110847, 2022.
- Deniz A. Bezgin, Steffen J. Schmidt, Nikolaus A. Adams. WENO3-NN: A maximum-order three-point data-driven weighted essentially non-oscillatory scheme. J. Comput. Physics, 452:110920, 2022.
- Magnus Svärd. Large Eddy Simulations by approximate weak entropy solutions. J. Comput. Physics, 448:110737, 2022.
- Mokbel Karam, Tony Saad. High-order pressure estimates for projection-based Navier-Stokes solvers. J. Comput. Physics, 452:110925, 2022.
- Ayaboe K. Edoh. A new kinetic-energy-preserving method based on the convective rotational form. J. Comput. Physics, 454:110971, 2022.