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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.