Prototypical graph contrastive learning

• Main Authors: LIN, Shuai, LIU, Chen, ZHOU, Pan, HU, Zi-Yuan, WANG, Shuojia, ZHAO, Ruihui, ZHENG, Yefeng, LIN, Liang, XING, Eric, LIANG, Xiaodan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Contrastive learning; Self-supervised learning; Graph representation learning; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9055; https://ink.library.smu.edu.sg/context/sis_research/article/10058/viewcontent/2022_TNNLS_PGCL.pdf
• Institution: Singapore Management University

Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. But in practice, precise graph annotations are generally very expensive and time-consuming. To address this issue, graph contrastive learning constructs instance discriminatio...