Title
Learning on Attribute-Missing Graphs
Abstract
Graphs with complete node attributes have been widely explored recently. While in practice, there is a graph where attributes of only partial nodes could be available and those of the others might be entirely missing. This attribute-missing graph is related to numerous real-world applications and there are limited studies investigating the corresponding learning problems. Existing graph learning m...
Year
DOI
Venue
2022
10.1109/TPAMI.2020.3032189
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keywords
DocType
Volume
Task analysis,Gallium nitride,Generative adversarial networks,Convolution,Recurrent neural networks,Linear programming
Journal
44
Issue
ISSN
Citations 
2
0162-8828
0
PageRank 
References 
Authors
0.34
39
6
Name
Order
Citations
PageRank
Xu Chen1271.67
Siheng Chen232427.85
Jiangchao Yao300.34
Huangjie Zheng472.78
Ya Zhang5134091.72
Ivor W. Tsang65396248.44