BindsNET/bindsnet
Simulation of spiking neural networks (SNNs) using PyTorch.
This tool helps researchers and machine learning practitioners design and simulate spiking neural networks (SNNs), which are inspired by biological brains. You can input various data types, like images for classification or observations from reinforcement learning environments, to train these SNNs. The output includes trained SNN models that can perform tasks like data discrimination, clustering, or controlling an agent.
1,659 stars. Actively maintained with 10 commits in the last 30 days.
Use this if you are a neuroscience researcher or ML practitioner exploring biologically inspired algorithms and want to simulate spiking neural networks for machine learning or reinforcement learning problems.
Not ideal if you primarily work with traditional artificial neural networks (ANNs) and are not specifically focused on brain-inspired SNNs or spike-timing-dependent plasticity.
Stars
1,659
Forks
342
Language
Python
License
AGPL-3.0
Category
Last pushed
Mar 12, 2026
Commits (30d)
10
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/BindsNET/bindsnet"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
fangwei123456/spikingjelly
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
neuromorphs/NIR
Neuromorphic Intermediate Representation reference implementation
norse/norse
Deep learning with spiking neural networks (SNNs) in PyTorch.
jeshraghian/snntorch
Deep and online learning with spiking neural networks in Python
synsense/rockpool
A machine learning library for spiking neural networks. Supports training with both torch and...