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  1. # decagon-pytorch
  2. ## Introduction
  3. [Decagon](https://github.com/mims-harvard/decagon)
  4. is a method for learning node embeddings in multimodal graphs,
  5. and is especially useful for link prediction in highly multi-relational
  6. settings.
  7. Decagon-PyTorch is a PyTorch reimplementation of the algorithm.
  8. ## Citing
  9. If you use this code in your research please cite this repository as:
  10. Adaszewski S. (2020) https://code.adared.ch/sadaszewski/decagon-pytorch
  11. ## References
  12. 1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018).
  13. [Modeling polypharmacy side effects with graph convolutional networks](https://academic.oup.com/bioinformatics/article/34/13/i457/5045770)
  14. Bioinformatics, 34(13), i457-i466.