Imbalanced graph classification with multi-scale oversampling graph neural networks

• Main Authors: MA, Rongrong, PANG, Guansong, CHEN, Ling
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Graph classification; Imbalanced learning; Oversampling; Graph neural networks; Computer Sciences; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/9764; https://ink.library.smu.edu.sg/context/sis_research/article/10764/viewcontent/2405.04903v2.pdf
• Institution: Singapore Management University

One main challenge in imbalanced graph classification is to learn expressive representations of the graphs in under-represented (minority) classes. Existing generic imbalanced learning methods, such as oversampling and imbalanced learning loss functions, can be adopted for enabling graph representat...