IF YOU WOULD LIKE TO GET AN ACCOUNT, please write an email to s dot adaszewski at gmail dot com. User accounts are meant only to report issues and/or generate pull requests. This is a purpose-specific Git hosting for ADARED projects. Thank you for your understanding!

Stanislaw Adaszewski f8a02191cb _clear_adjacency_matrix_except_rows() might yet be fast enough on the GPU.		4年前
docker	Start working on experiments/decagon_run.	4年前
docs	Update matrix-multiply.	4年前
experiments	Add Citing note.	4年前
src	_clear_adjacency_matrix_except_rows() might yet be fast enough on the GPU.	4年前
tests	_clear_adjacency_matrix_except_rows() might yet be fast enough on the GPU.	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.