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Stanislaw Adaszewski
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4 年之前 | |
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| docker | 4 年之前 | |
| docs | 4 年之前 | |
| experiments/decagon_run | 4 年之前 | |
| src | 4 年之前 | |
| tests | 4 年之前 | |
| .empty | 4 年之前 | |
| .gitignore | 4 年之前 | |
| README.md | 4 年之前 | |
| requirements.txt | 4 年之前 | |
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
- Zitnik, M., Agrawal, M., & Leskovec, J. (2018). Modeling polypharmacy side effects with graph convolutional networks Bioinformatics, 34(13), i457-i466.