peytontolbert/multiple-input-multiple-output-nets

PyTorch Implementation of the paper "MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition" published in NeurIPS 2023.

MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition

Nicolas Menet, Michael Hersche, Geethan Karunaratne, Luca Benini, Abu Sebastian, Abbas Rahimi

NeurIPS'23

This repository contains the implementation of MIMOConv and MIMOFormer. Details and instructions can be found in the corresponding folder.

[Paper]

Citation

If you use the work released here for your research, please cite our paper:

@article{menet2023mimo,
  title={MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition},
  author={Menet, Nicolas and Hersche, Michael and Karunaratne, Geethan and Benini, Luca and Sebastian, Abu and Rahimi, Abbas},
  journal={Advances in Neural Information Processing Systems (NeurIPS)},
  volume={36},
  year={2023}
}

License

Please refer to the LICENSE file for the licensing of our code.