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Stanislaw Adaszewski b439a46fc3 Use if constexpr to make stable_sort_impl() more compact. пре 4 година
docker Start working on experiments/decagon_run. пре 4 година
docs Add Batcher. пре 4 година
experiments Add first triacontagon experiment. пре 4 година
src Use if constexpr to make stable_sort_impl() more compact. пре 4 година
tests Mini fix. пре 4 година
.empty Initial commit. пре 4 година
.gitignore torch_stablesort_cpp seems to work. пре 4 година
README.md Add Citing note. пре 4 година
requirements.txt Start icosagon. пре 4 година

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.