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Stanislaw Adaszewski 56fdd9ffeb Make negative sampling more correct and more efficient at the same time. пре 4 година
docker Start working on experiments/decagon_run. пре 4 година
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experiments Add Citing note. пре 4 година
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tests Make negative sampling more correct and more efficient at the same time. пре 4 година
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README.md Add Citing note. пре 4 година
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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.

Citing

If you use this code in your research please cite this repository as:

Adaszewski S. (2020) https://code.adared.ch/sadaszewski/decagon-pytorch

References

  1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018). Modeling polypharmacy side effects with graph convolutional networks Bioinformatics, 34(13), i457-i466.