Graph Matching Based Graph Self-Supervised Learning for Molecular Property Prediction

Published in 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024

We propose a Graph Matching Based Graph Self-Supervised Learning (GMSSL) framework, which aims to comprehensively learn the structure and semantics of molecular graphs. Utilizing intra-graph and inter-graph convolution and graph matching methods, GMSSL demonstrates powerful molecular property prediction on multiple datasets.

Recommended citation: Hongxiang Lin, Yixiao Zhou, Huiying Hu, Zhicheng He, Runzhi Wu, Xiaoqing Lyu. (2024). "Graph Matching Based Graph Self-Supervised Learning for Molecular Property Prediction." 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Pages 7092-7094.
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