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
派生自 sadaszewski/decagon-pytorch
1
0
派生 0
代码 工单 0 合并请求 0 版本发布 0 百科 动态
您最多选择25个主题 主题必须以字母或数字开头，可以包含连字符 (-)，并且长度不得超过35个字符
76 提交
1 分支
866KB
目录树: dc92634830
分支列表 标签列表
${ item.name }
创建分支 ${ searchTerm }
从 'dc92634830'
${ noResults }
Stanislaw Adaszewski dc92634830 Same test with torch.nn.Sequential. 4 年前
docs Work on icosagon.trainprep. 4 年前
src Add first test for declayer. 4 年前
tests Same test with torch.nn.Sequential. 4 年前
.empty Initial commit. 4 年前
.gitignore Started implementing convolutions, with tests. 4 年前
README.md Update README.md 4 年前
requirements.txt Start icosagon. 4 年前

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.