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Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation
Graph Neural Networks (GNNs) are powerful for the representation learning of graph-structured data. Most of the GNNs use a message-passing scheme, where the embedding of a node is iteratively updated by aggregating the information from its neighbors. To achieve a better expressive capability of node...
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| Publicado no: | IJCAI (U S) |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7416665/ https://ncbi.nlm.nih.gov/pubmed/32782421 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.24963/ijcai.2020/194 |
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