Web: http://arxiv.org/abs/2202.08235

Sept. 22, 2022, 1:12 a.m. | Kaize Ding, Zhe Xu, Hanghang Tong, Huan Liu

cs.LG updates on arXiv.org arxiv.org

Graph neural networks, a powerful deep learning tool to model
graph-structured data, have demonstrated remarkable performance on numerous
graph learning tasks. To address the data noise and data scarcity issues in
deep graph learning, the research on graph data augmentation has intensified
lately. However, conventional data augmentation methods can hardly handle
graph-structured data which is defined in non-Euclidean space with
multi-modality. In this survey, we formally formulate the problem of graph data
augmentation and further review the representative techniques and …

arxiv augmentation data graph graph learning survey

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