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Stanislaw Adaszewski c1689b4985 Split decoders into cartesian and pairwise. пре 4 година
docs Better way to compute DecagonLayer. пре 4 година
src/decagon_pytorch Split decoders into cartesian and pairwise. пре 4 година
tests/decagon_pytorch Split decoders into cartesian and pairwise. 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

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.