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Stanislaw Adaszewski 3795545674 Start icosagon. 3 年前
docs Add train-val-test-diagram. 3 年前
src Start icosagon. 3 年前
tests Start icosagon. 3 年前
.empty Initial commit. 4 年前
.gitignore Started implementing convolutions, with tests. 4 年前
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requirements.txt Start icosagon. 3 年前

README.md

decagon-pytorch

Introduction

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 Bioinformatics, 34(13), i457-i466.