Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network

Bai Jiyang
Bai Jiyang
Ren Yuxiang
Ren Yuxiang
Cited by: 1|Views4

Abstract:

Graph neural networks (GNNs) have achieved outstanding performance in learning graph-structured data. Many current GNNs suffer from three problems when facing large-size graphs and using a deeper structure: neighbors explosion, node dependence, and oversmoothing. In this paper, we propose a general subgraph-based training framework, nam...More

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