Abstract: Graph contrastive learning (GCL) leverages semantic consistency as contrastive signals and has shown strong performance in semi-supervised node classification. However, real-world graphs ...
Abstract: Graph neural networks (GNNs) have obtained considerable attention due to their ability to leverage the inherent topological and node information present in graph data. While extensive ...
Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks ...
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