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News/Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors
arxiv
PublishedJune 2, 2026 at 4:00 AM

Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors

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arXiv:2410.09737v2 Announce Type: replace Abstract: A popular way to improve the expressive power of graph neural networks (GNNs) is to use Laplacian eigenvectors as additional node features, since they can serve both as structural identifiers and global coordinates of nodes. Properly handling the o

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