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!
sadaszewski1
/
decagon-pytorch
разклонено от sadaszewski/decagon-pytorch
1
0
Разклонения 0
Код Задачи 0 Заявки за сливане 0 Версии 0 Уики Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
169 Ревизии
1 Клон
866KB
ИН на ревизия: 058d4d43fb
Клонове Маркери
${ item.name }
Create branch ${ searchTerm }
от '058d4d43fb'
${ noResults }
Stanislaw Adaszewski 058d4d43fb Add _sparse_diag_cat(). преди 4 години
docker Start working on experiments/decagon_run. преди 4 години
docs Update matrix-multiply. преди 4 години
experiments Add Citing note. преди 4 години
src Add _sparse_diag_cat(). преди 4 години
tests Add _sparse_diag_cat(). преди 4 години
.empty Initial commit. преди 4 години
.gitignore Add test_timing_05(). преди 4 години
README.md Add Citing note. преди 4 години
requirements.txt Start icosagon. преди 4 години

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.