There are 8 repositories under snn topic.
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
Deep and online learning with spiking neural networks in Python
🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.
A PyTorch implementation of Spiking-YOLOv3. Two branches are provided, based on two common PyTorch implementation of YOLOv3(ultralytics/yolov3 & eriklindernoren/PyTorch-YOLOv3), with support for Spiking-YOLOv3-Tiny at present.
🔥 This repo compiles top conference papers and code for Spiking Neural Networks research. The project is actively evolving. 本仓库收集了脉冲神经网络领域的顶会顶刊论文和代码,正在持续更新中。
List of open source neuromorphic projects: SNN training frameworks, DVS handling routines and so on.
🔥🔥🔥A collection of some awesome public SNN(Spiking Neural Network) projects.
Repository collecting papers about neuromorphic hardware, such as ASIC and FPGA implementations of SNNs and stuff.
Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation
A paper list of spiking neural networks, including papers, codes, and related websites.
Experiments with spiking neural networks (SNNs) in PyTorch. See https://github.com/BINDS-LAB-UMASS/bindsnet for the successor to this project.
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
Basic SNN propogating spikes between LIF neurons
Spiking-DDPG trains an SNN for energy-efficient mapless navigation on Intel's Loihi neuromorphic processor.
Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network
The Spiking Reservoir (Liquid State Machine - LSM) Simulator
Code for the model presented in the paper "A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule"
DRL with population coded spiking neural network for optimal and energy-efficient continuous control.
spiking-neural-networks
Leaky Integrate and Fire (LIF) model implementation for FPGA
Quantization-aware training with spiking neural networks
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Spiking neural network system
code for generating data set ES-ImageNet with corresponding training code
A project dedicated to developing a hardware Integrated Circuit (IC) for a Spike Neural Network (SNN), powered by the RTL code generated by ChatGPT-4 with advanced optimizations.
Implementation of a Spiking Neural Network in Tensorflow.
High-performance Spiking Neural Networks Library Written From Scratch with C++ and Python Interfaces.
A simple from scratch implementation of a Spiking-Neural-Network with STDP in Python which is beeing trained on MNIST.