Node Similarity Preserving Graph Convolutional Networks
WSDM, pp. 148-156, 2021.
Graph Neural Networks (GNNs) have achieved tremendous success in various real-world applications due to their strong ability in graph representation learning. GNNs explore the graph structure and node features by aggregating and transforming information within node neighborhoods. However, through theoretical and empirical analysis, we r...More
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