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
forked from sadaszewski/decagon-pytorch
1
0
Fork 0
Code Issues 0 Pull Requests 0 Releases 0 Wiki 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.
141 Commits
1 Branch
866KB
Tree: 8aafb6fa01
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from '8aafb6fa01'
${ noResults }
Stanislaw Adaszewski 8aafb6fa01 Clean up _equal(). 4 years ago
docker Start working on experiments/decagon_run. 4 years ago
docs Add icosagon-reltype-rules. 4 years ago
experiments/decagon_run Start working on experiments/decagon_run. 4 years ago
src Clean up _equal(). 4 years ago
tests Make _equal() much faster. 4 years ago
.empty Initial commit. 4 years ago
.gitignore Add icosagon classes diagram. 4 years ago
README.md Update README.md 4 years ago
requirements.txt Start icosagon. 4 years ago

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.

References

  1. Zitnik, M., Agrawal, M., & Leskovec, J. (2018). Modeling polypharmacy side effects with graph convolutional networks Bioinformatics, 34(13), i457-i466.