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
forkato da sadaszewski/decagon-pytorch
1
0
Forka 0
Codice Problemi 0 Pull Requests 0 Rilasci 0 Wiki Attività
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.
28 Commit
1 Ramo (Branch)
866KB
Albero (Tree): b1245e1a73
Rami (Branch) Tag
${ item.name }
Crea branch ${ searchTerm }
da 'b1245e1a73'
${ noResults }
Stanislaw Adaszewski b1245e1a73 Add a diagram. 4 anni fa
docs Add a diagram. 4 anni fa
src/decagon_pytorch Add support for multiple input_dim in MultiDGCA. 4 anni fa
tests/decagon_pytorch Add support for multiple input_dim in MultiDGCA. 4 anni fa
.empty Initial commit. 4 anni fa
.gitignore Started implementing convolutions, with tests. 4 anni fa
README.md Update README.md 4 anni fa

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.