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Stanislaw Adaszewski dc92634830 Same test with torch.nn.Sequential. пре 4 година
docs Work on icosagon.trainprep. пре 4 година
src Add first test for declayer. пре 4 година
tests Same test with torch.nn.Sequential. пре 4 година
.empty Initial commit. пре 4 година
.gitignore Started implementing convolutions, with tests. пре 4 година
README.md Update README.md пре 4 година
requirements.txt Start icosagon. пре 4 година

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.