P-K-GCN integrates continuous spline GCN, Koopman linearization, and physics augmentation for spatiotemporal super-resolution on irregular geometries, claiming theoretical error reduction via Rademacher complexity bounds and superior accuracy on cardiac electrodynamics.
arXiv preprint arXiv:2507.03855 , year=
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P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network for Deep Spatiotemporal Super-resolution
P-K-GCN integrates continuous spline GCN, Koopman linearization, and physics augmentation for spatiotemporal super-resolution on irregular geometries, claiming theoretical error reduction via Rademacher complexity bounds and superior accuracy on cardiac electrodynamics.