Web: http://arxiv.org/abs/2012.08752

Jan. 24, 2022, 2:10 a.m. | Yu Zhou, Haixia Zheng, Xin Huang, Shufeng Hao, Dengao Li, Jumin Zhao

cs.LG updates on arXiv.org arxiv.org

Graph neural networks provide a powerful toolkit for embedding real-world
graphs into low-dimensional spaces according to specific tasks. Up to now,
there have been several surveys on this topic. However, they usually lay
emphasis on different angles so that the readers can not see a panorama of the
graph neural networks. This survey aims to overcome this limitation, and
provide a comprehensive review on the graph neural networks. First of all, we
provide a novel taxonomy for the graph neural …

arxiv graph graph neural networks networks neural neural networks taxonomy trends

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