A class-aware representation refinement framework for graph classification

Graph Neural Networks (GNNs) are widely used for graph representation learning. Despite its prevalence, GNN suffers from two drawbacks in the graph classification task, the neglect of graph-level relationships, and the generalization issue. Each graph is treated separately in GNN message passing/gra...

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Main Authors: Xu, Jiaxing, Ni, Jinjie, Ke, Yiping
其他作者: College of Computing and Data Science
格式: Article
語言:English
出版: 2024
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在線閱讀:https://hdl.handle.net/10356/180546
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