Co-Attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data. However, previous works mainly focused on understanding single graph inputs while many real-world applications require pair-wise analysis for graph-structured data (e.g., scene graph match...
| Auteurs principaux: | , , , |
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| Format: | Article |
| Langue: | English |
| Publié: |
IEEE
2023-01-01
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| Collection: | IEEE Access |
| Sujets: | |
| Accès en ligne: | https://ieeexplore.ieee.org/document/10196307/ |