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!
Vous ne pouvez pas sélectionner plus de 25 sujets Les noms de sujets doivent commencer par une lettre ou un nombre, peuvent contenir des tirets ('-') et peuvent comporter jusqu'à 35 caractères.
Stanislaw Adaszewski d7d442c5e3 New fixed_unigram_candidate_sampler() still requires work. il y a 4 ans
docker Start working on experiments/decagon_run. il y a 4 ans
docs Add Batcher. il y a 4 ans
experiments Add first triacontagon experiment. il y a 4 ans
src New fixed_unigram_candidate_sampler() still requires work. il y a 4 ans
tests Work on fixed_unigram_candidate_sampler_new(). il y a 4 ans
.empty Initial commit. il y a 4 ans
.gitignore Add test_timing_05(). il y a 4 ans
README.md Add Citing note. il y a 4 ans
requirements.txt Start icosagon. il y a 4 ans

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.