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On the Global Self-attention Mechanism for Graph Convolutional Networks
[article]
2020
arXiv
pre-print
Applying Global Self-attention (GSA) mechanism over features has achieved remarkable success on Convolutional Neural Networks (CNNs). However, it is not clear if Graph Convolutional Networks (GCNs) can similarly benefit from such a technique. In this paper, inspired by the similarity between CNNs and GCNs, we study the impact of the Global Self-attention mechanism on GCNs. We find that consistent with the intuition, the GSA mechanism allows GCNs to capture feature-based vertex relations
arXiv:2010.10711v1
fatcat:qg2yijlvcjczfgqiglckhfdp2y