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Stanislaw Adaszewski a5b8701a0d Add some debug output for profiling, the bottleneck is in DecodeLayer but also comes generally from computing always all nodes.		4 년 전
docker	Start working on experiments/decagon_run.	4 년 전
docs	Add icosagon-reltype-rules.	4 년 전
experiments/decagon_run	Shuffle.	4 년 전
src	Add some debug output for profiling, the bottleneck is in DecodeLayer but also comes generally from computing always all nodes.	4 년 전
tests	Add some debug output for profiling, the bottleneck is in DecodeLayer but also comes generally from computing always all nodes.	4 년 전
.empty	Initial commit.	4 년 전
.gitignore	Add icosagon classes diagram.	4 년 전
README.md	Update README.md	4 년 전
requirements.txt	Start icosagon.	4 년 전

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

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