1. Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations;Raissi;J. Comput. Phys.,2019
2. Ppinn: parareal physics-informed neural network for time-dependent pdes;Meng;Comput. Methods Appl. Mech. Eng.,2020
3. Neural operator: learning maps between function spaces with applications to pdes;Kovachki;J. Mach. Learn. Res.,2023
4. Characterizing possible failure modes in physics-informed neural networks (characterizing-pinns-failure-modes);Krishnapriyan,2021
5. Physics-data combined machine learning for parametric reduced-order modelling of nonlinear dynamical systems in small-data regimes;Fu;Comput. Methods Appl. Mech. Eng.,2023