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# decagon-pytorch |
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## Introduction |
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[Decagon](https://github.com/mims-harvard/decagon) |
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is a method for learning node embeddings in multimodal graphs, |
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and is especially useful for link prediction in highly multi-relational |
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settings. |
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Decagon-PyTorch is a PyTorch reimplementation of the algorithm. |
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## References |
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1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018). |
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[Modeling polypharmacy side effects with graph convolutional networks](https://academic.oup.com/bioinformatics/article/34/13/i457/5045770) |
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Bioinformatics, 34(13), i457-i466. |
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