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Stanislaw Adaszewski 82d5c06eee Fix aggregation of representations from different edge types.		4年前
docker	Start working on experiments/decagon_run.	4年前
docs	Work on required vertices per layer.	4年前
experiments	Add Citing note.	4年前
src	Fix aggregation of representations from different edge types.	4年前
tests	Make work convolve() in new model.	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

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