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+Original authors have uploaded their code here https://github.com/vlawhern/arl-eegmodels
+
+# EEGNet
+PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces
+
+## Requirements
+* Python 2
+* Dataset of your own choice, works well with BCI Competition 3 Dataset 2.
+* Pytorch 0.2+
+* Jupyter notebook
+
+## Usage
+* GPU - 
+Just ```shift+enter``` everything.
+* No GPU -
+Remove all ```.cuda(0)``` before running. 
+
+## Notes
+* <strike>I found ELU to work inferior, would not recommend. Linear units work better than ReLU as well.</strike>
+* I found that ELU/Linear/ReLU are similar in performance. 
+
+## Results
+* BCI Competition 3 Dataset 2 - Fmeasure (0.402)
+
+## Credits
+* Original paper - https://arxiv.org/abs/1611.08024
+* PyTorch documentation.
+
+Hope this helped you. Raise an issue if you spot errors or contact sriram@ucsd.edu.