Abstract: Graph neural networks greatly facilitate data processing in homogeneous and heterogeneous graphs. However, training GNNs on large-scale graphs poses a significant challenge to computing ...
Abstract: Graph neural networks (GNNs) witness impressive performances on homophilic graphs characterized by a higher number of edges connecting nodes of similar class labels. A decline in the ...
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