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Yingying Wan

2 accepted papers

2022

Information Augmentation for Few-shot Node Classification

IJCAI 2022poster

Although meta-learning and metric learning have been widely applied for few-shot node classification (FSNC), some limitations still need to be addressed, such as expensive time costs for the meta-train and difficult of exploring the complex structure inherent the graph data. To address in issues, th…

Cited by 11SourcePDFScholar
2022

Multi-view Unsupervised Graph Representation Learning

IJCAI 2022poster

Both data augmentation and contrastive loss are the key components of contrastive learning. In this paper, we design a new multi-view unsupervised graph representation learning method including adaptive data augmentation and multi-view contrastive learning, to address some issues of contrastive lear…

Cited by 0SourcePDFScholar