Graph neural networks have emerged as a leading paradigm for inferring node labels in complex relational data. By extending convolutional and attention operations to arbitrary graph structures, these ...
Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
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