haoran-zha / Awesome-Spiking-Neural-Networks-Hub
The comprehensive bilingual (EN/中文) hub for Spiking Neural Networks — 340+ papers, models, neuromorphic hardware, datasets, tools & research groups.
Why this job: name: awesome; topics: awesome-list, awesome
What it does
Conventional deep networks (ANNs) pass continuous numbers between neurons at every layer, synchronously, every forward pass. A Spiking Neural Network instead communicates with discrete, binary events — "spikes" — in time, exactly like biological neurons. A spiking neuron integrates incoming current onto a *membrane potential*; when that potential crosses a threshold, it emits a single spike and resets. Nothing happens when there is no spike.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 28 days ago
- Stars
- 119
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 58% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- None
- No issues filed
- Pull requests
- 0 merged
- 0 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 58%
- HTML 42%
Topics
- awesome
- awesome-list
- brain-inspired-computing
- deep-learning
- event-camera
- machine-learning
- neural-networks
- neuromorphic-computing
- neuromorphic-hardware
- paper-list
- snn
- spiking-neural-networks
Project record
- JobLists and guides
- StatusListed
- Commits28
- Forks1
- Watching0
- Stars in 28 days+2
- CreatedJul 20, 2026
- First seen by usNov 7, 2026
- CheckedNov 8, 2026