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Added in acknowledgments.
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William L Hamilton 2017-06-09 11:18:53 +01:00 committed by GitHub
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@ -70,3 +70,9 @@ Note that the full log outputs and stored embeddings can be 5-10Gb in size (on t
The unsupervised variants of GraphSAGE will output embeddings to the logging directory as described above.
These embeddings can then be used in downstream machine learning applications.
The `eval_scripts` directory contains examples of feeding the embeddings into simple logistic classifiers.
#### Acknowledgements
The original version of this code base was originally forked from https://github.com/tkipf/gcn/, and we owe many thanks to Thomas Kipf for making his code available.
We also thank Yuanfang Li and Xin Li who contributed to a course project that was based on this work.
Please see the [paper](https://arxiv.org/pdf/1706.02216.pdf) for funding details and additional (non-code related) acknowledgements.