You-Min Tang

Physics-informed hybrid neural networks with data constraints: A case study on lorenz63.

Physics-Informed Neural Networks (PINNs) are a hybrid modeling approach that integrates physical priors into neural networks. By encoding governing equations as soft constraint terms into the loss function, this method accomplishes organic integration of data-driven approaches with physical laws. PINNs demonstrate sign...

The Importance of Subsurface Thermal Effects to Indian Ocean Dipole Prediction Revealed by a Skillful Three-Dimensional Deep Learning Model