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Neural networks trained to solve supervised learning tasks while respecting given laws of physics described by general nonlinear partial differential equations.
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 Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning Mara Daniels Liam Hodgkinson Michael Mahoney | |||
 Hierarchical Physics-Embedded Learning for Spatiotemporal Dynamical Systems Xizhe Wang Xiaobin Song Qingshan Jia Hongbo Zhao Benben Jiang | |||
 Neural Networks as Surrogate Solvers for Time-Dependent Accretion Disk DynamicsAstrophysical Journal Letters (ApJL), 2025 | |||
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