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!
Você não pode selecionar mais de 25 tópicos Os tópicos devem começar com uma letra ou um número, podem incluir traços ('-') e podem ter até 35 caracteres.
Stanislaw Adaszewski cef1d1110a Add more tests in test_bulkdec. 4 anos atrás
docker Start working on experiments/decagon_run. 4 anos atrás
docs Performance tests. 4 anos atrás
experiments Add Citing note. 4 anos atrás
src Add bulkdec. 4 anos atrás
tests Add more tests in test_bulkdec. 4 anos atrás
.empty Initial commit. 4 anos atrás
.gitignore Add test_timing_05(). 4 anos atrás
README.md Add Citing note. 4 anos atrás
requirements.txt Start icosagon. 4 anos atrás

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.