GraphSAINT: Graph Sampling Based Inductive Learning Method

10 Jul 2019Hanqing ZengHongkuan ZhouAjitesh SrivastavaRajgopal KannanViktor Prasanna

Graph Convolutional Networks (GCNs) are powerful models for learning representations of attributed graphs. To scale GCNs to large graphs, state-of-the-art methods use various layer sampling techniques to alleviate the "neighbor explosion" problem during minibatch training... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Node Classification PPI GraphSAINT F1 99.50 # 1
Node Classification Reddit GraphSAINT Accuracy 97.0% # 2