Surrogate modeling of pantograph-catenary system interactions

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

Natural Sciences, Computer Science, Physics +16

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

Nature Machine Intelligence · 2021 · 2.8K citations · Full text

Computing, Computer Science, Mathematics +10

Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next

Salvatore Cuomo, Vincenzo Schiano Di Cola, Fabio Giampaolo et al. · Journal of Scientific Computing · 2022 · 2.3K citations · Full text

Computing, Computer Science, Physics +16

Fourier Neural Operator for Parametric Partial Differential Equations

Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli et al. · arXiv (Cornell University) · 2020 · 1.1K citations · Full text

Natural Sciences, Mathematics, Physics +17

KAN: Kolmogorov-Arnold Networks

Ziming Liu, Yixuan Wang, Sachin Vaidya et al. · arXiv (Cornell University) · 2024 · 508 citations · Full text

Computing, Computer Science, Mathematics +17