Introduces coarse and fine feature-graph alignment notions to enable subgraph sampling that preserves Laplacian trace and spectral properties for improved GNN transferability without relying on complete graph structure.
Efficient sampling set selection for bandlimited graph signals using graph spectral proxies
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Sampling Transferable Graph Neural Networks with Limited Graph Information
Introduces coarse and fine feature-graph alignment notions to enable subgraph sampling that preserves Laplacian trace and spectral properties for improved GNN transferability without relying on complete graph structure.