ANalogy subGraph Embedding Learning (GraphANGEL)

Code for ICLR'22 "Inductive Relation Prediction Using Analogy Subgraph Embeddings"

This includes pytorch implementations of light and heavy (i.e., original) versions of GraphANGEL model. This is the experiment code in the following work:

Inductive Relation Prediction Using Analogy Subgraph Embeddings
Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Quan Gan, Zheng Zhang, Yong Yu, David Wipf.
ICLR 2022

We are working on developing a lighter and easier version of GraphANGEL in the AwesomeStructure project.

References

If you find this work helpful in your research, please consider citing the following paper. The bibtex are listed below:

@inproceedings{jin2021inductive,
  title={Inductive Relation Prediction Using Analogy Subgraph Embeddings},
  author={Jin, Jiarui and Wang, Yangkun and Du, Kounianhua and Zhang, Weinan and Zhang, Zheng and Wipf, David and Yu, Yong and Gan, Quan},
  booktitle={International Conference on Learning Representations},
  year={2021}
}