Structure-Aware Multi-Hop Graph Convolution for Graph Neural Networks
We present a spatial graph convolution (GC) to classify signals on a graph. Existing GC methods are limited in using the structural information in the feature space. Furthermore, GCs only aggregate features from one-hop neighboring nodes to the target node in their single step. In this paper, we pro...
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| Auteurs principaux: | , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
IEEE
2022-01-01
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| Collection: | IEEE Access |
| Sujets: | |
| Accès en ligne: | https://ieeexplore.ieee.org/document/9706184/ |
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