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Mismatch-Tolerant SNNs

This repository contains the code used in "Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic Computing".

Note

The code provided in this repository is experimental and intended as a resource for readers interested in studying the methodology proposed. Please note that some of the terminology used in the code may differ from that used in the paper.

Repository Content

Below is a brief description of the main files included in the repository:

  • models.py: Implementation of the proposed mismatch-tolerant architecture and of the spiking MLP used as baseline.
  • train.py: Script for training the models.

Citation

@misc{boccato2024geneticmotifsblueprintmismatchtolerant,
      title={Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic Computing}, 
      author={Tommaso Boccato and Dmitrii Zendrikov and Nicola Toschi and Giacomo Indiveri},
      year={2024},
      eprint={2410.19403},
      archivePrefix={arXiv},
      primaryClass={cs.NE},
      url={https://arxiv.org/abs/2410.19403}, 
}