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cs.LG2024
When Graph Neural Networks Meet Dynamic Mode Decomposition
Dai Shi, Lequan Lin, Andi Han +3
Graph Neural Networks (GNNs) have emerged as fundamental tools for a wide range of prediction tasks on graph-structured data. Recent studies have drawn analogies between GNN featur…
cs.LG2024
Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks
Dai Shi, Andi Han, Lequan Lin +3
Physics-informed Graph Neural Networks have achieved remarkable performance in learning through graph-structured data by mitigating common GNN challenges such as over-smoothing, ov…