NDGGNET-A Node Independent Gate based Graph Neural Networks. (arXiv:2205.05348v1 [cs.LG])

Web: http://arxiv.org/abs/2205.05348

Graph Neural Networks (GNNs) is an architecture for structural data, and has
been adopted in a mass of tasks and achieved fabulous results, such as link
prediction, node classification, graph classification and so on. Generally, for
a certain node in a given graph, a traditional GNN layer can be regarded as an
aggregation from one-hop neighbors, thus a set of stacked layers are able to
fetch and update node status within multi-hops. For nodes with sparse
connectivity, it is difficult …

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