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Stanislaw Adaszewski 2d92cc95bb Add test_sparse_dropout_grap_conv_activation() 4 anni fa
src/decagon_pytorch Add test_sparse_dropout_grap_conv_activation() 4 anni fa
tests/decagon_pytorch Add test_sparse_dropout_grap_conv_activation() 4 anni fa
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README.md Update README.md 4 anni fa

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.