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Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

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MAP-SNN

MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks [1]

overview

Requirement

  • Python 3.6
  • Pytorch
  • SnnTorch
  • SHD dataste [2]
  • N-MNIST dataset [3]

Reference

[1] C. Yu, Y. Du, M. Chen, A. Wang, G. Wang, and E. Li, “MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks,” Frontiers in Neuroscience, vol. 16, 2022. Available: https://www.frontiersin.org/articles/10.3389/fnins.2022.945037

[2] Spiking Heidelberg Datasets
https://zenkelab.org/resources/spiking-heidelberg-datasets-shd/

[3] Neuromorphic-MNIST (N-MNIST) Dataset
https://www.garrickorchard.com/datasets/n-mnist

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Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks

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