In the tutorial for semi-supervised learning with GCN, variable graphs are provided to GNN from FeaturedGraph, which contains a graph and node features. Each FeaturedGraph object can contain different ...
Graph convolutional network (GCN) has been successfully applied to many graph-based applications; however, training a large-scale GCN remains challenging. Current SGD-based algorithms suffer from ...
Abstract: Graph Convolutional Networks (GCNs) have shown great results but come with large computation costs and memory overhead. Recently, sampling-based approaches have been proposed to alter input ...
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