CASIA OpenIR  > 学术期刊  > IEEE/CAA Journal of Automatica Sinica
Variational Gridded Graph Convolution Network for Node Classification
Xiaobin Hong; Tong Zhang; Zhen Cui; Jian Yang
发表期刊IEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2021
卷号8期号:10页码:1697-1708
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.
关键词Graph coarsening gridding node classification random walk variational convolution
DOI10.1109/JAS.2021.1004201
引用统计
被引频次:10[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/45383
专题学术期刊_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.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
JAS-2021-0043.pdf(2419KB)期刊论文出版稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Xiaobin Hong]的文章
[Tong Zhang]的文章
[Zhen Cui]的文章
百度学术
百度学术中相似的文章
[Xiaobin Hong]的文章
[Tong Zhang]的文章
[Zhen Cui]的文章
必应学术
必应学术中相似的文章
[Xiaobin Hong]的文章
[Tong Zhang]的文章
[Zhen Cui]的文章
相关权益政策
暂无数据
收藏/分享
文件名: JAS-2021-0043.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。