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Stanislaw Adaszewski aa3cc1f3ad Reimplement FastConvLayer.		4 yıl önce
docker	Start working on experiments/decagon_run.	4 yıl önce
docs	Update matrix-multiply.	4 yıl önce
experiments	Add Citing note.	4 yıl önce
src	Reimplement FastConvLayer.	4 yıl önce
tests	Add test_fast_graph_conv_03() and test_fast_graph_conv_04().	4 yıl önce
.empty	Initial commit.	4 yıl önce
.gitignore	Add test_timing_05().	4 yıl önce
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requirements.txt	Start icosagon.	4 yıl önce

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.