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Abstract: Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost.

Abstract: Compared with Static Knowledge Graphs, Temporal Knowledge Graphs need to pay more attention to the time when facts occur and these facts will change over time. However, existing models lack ...

This code was tested with PyTorch 2.0.1, cuda 11.8 and torch_geometrics 2.3.1. Note that ${PROJECT_DIR} refers to this directory. The following section outlines the graph-to-graph transformation ...