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!
Nie możesz wybrać więcej, niż 25 tematów Tematy muszą się zaczynać od litery lub cyfry, mogą zawierać myślniki ('-') i mogą mieć do 35 znaków.
Stanislaw Adaszewski c210be41b3 Add databatch. 4 lat temu
docker Start working on experiments/decagon_run. 4 lat temu
docs Performance tests. 4 lat temu
experiments Add Citing note. 4 lat temu
src Add databatch. 4 lat temu
tests Add databatch. 4 lat temu
.empty Initial commit. 4 lat temu
.gitignore Add test_timing_05(). 4 lat temu
README.md Add Citing note. 4 lat temu
requirements.txt Start icosagon. 4 lat temu

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.