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選択できるのは25トピックまでです。 トピックは、先頭が英数字で、英数字とダッシュ('-')を使用した35文字以内のものにしてください。
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.