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Arxiv
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Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective
- Graph neural networks (GNNs) face challenges of heterogeneity and heterophily.
- Heterogeneity involves diverse node and edge types in a graph.
- Heterophily refers to connected nodes having dissimilar attributes or labels.
- The proposed Heterogeneous Heterophilic Spectral Graph Neural Network (H2SGNN) addresses these challenges using local and global filtering.
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