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README.md
@@ -101,3 +101,5 @@ See `tabular.ipynb` for an example to run sparse to sparse training on tabular d
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We would like to acknowledge the following code repositories on which our code is based:
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- [Random_Pruning](https://github.com/VITA-Group/Random_Pruning)
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- [STR](https://github.com/RAIVNLab/STR)
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+- [GCN](https://github.com/meliketoy/graph-cnn.pytorch)
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+- [Algorithmic Data](https://github.com/ejmichaud/grokking-squared/blob/main/notebooks/erics-implementation.ipynb)
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