norse
bindsnet
norse | bindsnet | |
---|---|---|
1 | 1 | |
61 | 1,433 | |
- | 1.7% | |
0.0 | 8.6 | |
almost 2 years ago | 5 days ago | |
Python | Python | |
GNU Lesser General Public License v3.0 only | GNU Affero General Public License v3.0 |
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norse
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Don't Mess with Backprop: Doubts about Biologically Plausible Deep Learning
If you are interested in deep learning with spiking neural networks there is also the norse framework: https://github.com/electronicvisions/norse
bindsnet
What are some alternatives?
snntorch - Deep and online learning with spiking neural networks in Python
Spiking-Neural-Network - Pure python implementation of SNN
spikingjelly - SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
norse - Deep learning with spiking neural networks (SNNs) in PyTorch.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
OpenWorm - Repository for the main Dockerfile with the OpenWorm software stack and project-wide issues
Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP - 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.