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guillaume-chevalier/Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP

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What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

4 mentions on Hacker News by 3 people: 1 story, 3 comments · first 2019-08-11 · latest 2023-05-24

Mentions per year 4 mentions · busiest year 2019 (3)
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  1. Check out SNN + Hebbian Learning: - https://arxiv.org/abs/2211.15386 - https://www.sciencedirect.com/science/article/abs/pii/S08936... - https://github.com/guillaume-chevalier/Spiking-Neural-Networ...
    comment by scrum-treats · 2023-05-24 · in Ask HN: Is our brain result of swarm intelligence from neurons?
  2. > "The relationship of spike-time-dependent plasticity to other models requires further clarifying work" - I got something for that, in fact I think I discovered that backpropagation engenders STDP: https://github.com/guillaume-chevalier/Sp…
    comment by GChevalier · 2019-08-11 · in Theories of Error Back-Propagation in the Brain
  3. > "The relationship of spike-time-dependent plasticity to other models requires further clarifying work" - I got something for that, in fact I think I discovered that backpropagation engenders STDP: https://github.com/guillaume-chevalier/Sp…
    comment by GChevalier · 2019-08-11 · in Theories of Error Back-Propagation in the Brain