Variational Gridded Graph Convolution Network for Node Classification

doi:10.1109/JAS.2021.1004201

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	Variational Gridded Graph Convolution Network for Node Classification
	Xiaobin Hong; Tong Zhang; Zhen Cui; Jian Yang
刊名	IEEE/CAA Journal of Automatica Sinica
	2021
卷号	8 期号:10 页码:1697-1708
关键词	Graph coarsening gridding node classification random walk variational convolution
ISSN号	2329-9266
DOI	10.1109/JAS.2021.1004201
英文摘要	The existing graph convolution methods usually suffer high computational burdens, large memory requirements, and intractable batch-processing. In this paper, we propose a high-efficient variational gridded graph convolution network (VG-GCN) to encode non-regular graph data, which overcomes all these aforementioned problems. To capture graph topology structures efficiently, in the proposed framework, we propose a hierarchically-coarsened random walk (hcr-walk) by taking advantage of the classic random walk and node/edge encapsulation. The hcr-walk greatly mitigates the problem of exponentially explosive sampling times which occur in the classic version, while preserving graph structures well. To efficiently encode local hcr-walk around one reference node, we project hcr-walk into an ordered space to form image-like grid data, which favors those conventional convolution networks. Instead of the direct 2-D convolution filtering, a variational convolution block (VCB) is designed to model the distribution of the random-sampling hcr-walk inspired by the well-formulated variational inference. We experimentally validate the efficiency and effectiveness of our proposed VG-GCN, which has high computation speed, and the comparable or even better performance when compared with baseline GCNs.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/45383]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Xiaobin Hong,Tong Zhang,Zhen Cui,et al. Variational Gridded Graph Convolution Network for Node Classification[J]. IEEE/CAA Journal of Automatica Sinica,2021,8(10):1697-1708.
APA	Xiaobin Hong,Tong Zhang,Zhen Cui,&Jian Yang.(2021).Variational Gridded Graph Convolution Network for Node Classification.IEEE/CAA Journal of Automatica Sinica,8(10),1697-1708.
MLA	Xiaobin Hong,et al."Variational Gridded Graph Convolution Network for Node Classification".IEEE/CAA Journal of Automatica Sinica 8.10(2021):1697-1708.