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選択できるのは25トピックまでです。 トピックは、先頭が英数字で、英数字とダッシュ('-')を使用した35文字以内のものにしてください。
Stanislaw Adaszewski 14321daf62 Improved dispatch. 4年前
docker Start working on experiments/decagon_run. 4年前
docs Add Batcher. 4年前
experiments Add first triacontagon experiment. 4年前
src Improved dispatch. 4年前
tests Mini fix. 4年前
.empty Initial commit. 4年前
.gitignore Add test_timing_05(). 4年前
README.md Add Citing note. 4年前
requirements.txt Start icosagon. 4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.

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.