Harnessing collective structure knowledge in data augmentation for graph neural networks

• Main Authors: MA, Rongrong, PANG, Guansong, CHEN, Ling
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Data augmentation; Graph neural networks; Graph representation learning; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/9289; https://ink.library.smu.edu.sg/context/sis_research/article/10289/viewcontent/HarnessingCollectiveStructureK_GNN_sv.pdf
• Institution: Singapore Management University

Graph neural networks (GNNs) have achieved state-of-the-art performance in graph representation learning. Message passing neural networks, which learn representations through recursively aggregating information from each node and its neighbors, are among the most commonly-used GNNs. However, a wealt...