P-K-GCN: Physics-augmented Koopman-enhanced Graph Convolutional Network

P-K-GCN enables high-fidelity spatiotemporal super-resolution on irregular geometries by combining graph convolutional networks with Koopman operator theory. It incorporates a physics-based loss to enforce adherence to physical laws, reducing super-resolution error through improved generalization and accuracy, as validated in cardiac electrodynamics reconstruction.