DNSD replaces the sheaf Laplacian with a sheaf adjacency operator, adds normalization and gating, and empirically outperforms GNN and NSD baselines by up to 30 percentage points on synthetic long-range graph tasks while also improving on real-world benchmarks.
Bundle Neural Networks for message diffusion on graphs
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Transductive Sharpening adds an entropy-minimization term on unlabeled-node predictions to the training objective for graph node classification.
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