Repository: SE-PINN
Summary: The mathematical properties of normality, symmetry, and orthogonality are integrated into a neural network itself via a custom loss function and a custom architectural layer in PyTorch so that its predictions respect these properties by design.
Graphic: This is an animation of how the predictions of a model change as it is trained. Visit the repository to view the same animation for a less naive model that respects exact symmetry.
