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Stanislaw Adaszewski 2188dc7ae2 Basic constructor test for DecagonLayer passes. vor 4 Jahren
docs Better way to compute DecagonLayer. vor 4 Jahren
src/decagon_pytorch Basic constructor test for DecagonLayer passes. vor 4 Jahren
tests/decagon_pytorch Basic constructor test for DecagonLayer passes. vor 4 Jahren
.empty Initial commit. vor 4 Jahren
.gitignore Started implementing convolutions, with tests. vor 4 Jahren
README.md Update README.md vor 4 Jahren

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.