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@ -12,14 +12,14 @@ ResMLP obtain good performance given its simplicity:
<img width="900" src=".github/resmlp.png">
</p>
For details see [ResMLP: Feedforward networks for image classification with data-efficient training](https://arxiv.org/abs/2105.03404) by Hugo Touvron, Piotr Bojanowski, Mathilde Caron, Matthieu Cord, Alaaeldin El-Nouby, Edouard Grave, Armand Joulin, Gabriel Synnaeve, Jakob Verbeek and Hervé Jégou.
For details see [ResMLP: Feedforward networks for image classification with data-efficient training](https://arxiv.org/abs/2105.03404) by Hugo Touvron, Piotr Bojanowski, Mathilde Caron, Matthieu Cord, Alaaeldin El-Nouby, Edouard Grave, Gautier Izacard, Armand Joulin, Gabriel Synnaeve, Jakob Verbeek and Hervé Jégou.
If you use this code for a paper please cite:
```
@article{touvron2021resmlp,
title={ResMLP: Feedforward networks for image classification with data-efficient training},
author={Hugo Touvron and Piotr Bojanowski and Mathilde Caron and M. Cord and Alaaeldin El-Nouby and Edouard Grave and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Herv'e J'egou},
author={Hugo Touvron and Piotr Bojanowski and Mathilde Caron and Matthieu Cord and Alaaeldin El-Nouby and Edouard Grave and Gautier Izacard and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Herv'e J'egou},
journal={arXiv preprint arXiv:2105.03404},
year={2021},
}