2 papers
cs.LG2026
Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations
Xujia Chen, Xinyue Hu, Letian Chen +2
Physics-informed neural networks (PINNs) incorporate governing equations into neural-network training and can approximate PDE solutions without requiring large observational datase…
cs.LG2026
Curriculum Learning of Physics-Informed Neural Networks based on Spatial Correlation
Xujia Chen, Xinyue Hu, Letian Chen +2
Physics-Informed Neural Networks (PINNs) combine deep learning with physical constraints for solving partial differential equations (PDEs), and are widely applied in fluid mechanic…