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