Co-embedding of Nodes and Edges with Graph Neural Networks

@article{Jiang2020CoembeddingON,
  title={Co-embedding of Nodes and Edges with Graph Neural Networks},
  author={Xiaodong Jiang and Ronghang Zhu and Pengsheng Ji and Sheng Li},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2020},
  volume={PP}
}
Graph is ubiquitous in many real world applications ranging from social network analysis to biology. How to correctly and effectively learn and extract information from graph is essential for a large number of machine learning tasks. Graph embedding is a way to transform and encode data structure in high dimensional and Non-Euclidean feature space to a low dimensional and structural space. We have witnessed a huge surge of such embedding methods, from statistical approaches to recent deep… Expand

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