DYNAMO-GAT prunes GNN attention edges between highly correlated nodes to prevent oversmoothing, but its main theoretical lemma contradicts its goal and its accuracy claims exceed its own table.
Convergence rates of neural networks for supervised learning on manifolds
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A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks
DYNAMO-GAT prunes GNN attention edges between highly correlated nodes to prevent oversmoothing, but its main theoretical lemma contradicts its goal and its accuracy claims exceed its own table.