There are 3 repositories under spiking-neural-network topic.
🚀🚀🚀 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.
Offical implementation of "Spike-driven Transformer" (NeurIPS2023)
实现一种多Lora权值集成切换+Zero-Finetune零微调增强的跨模型技术方案,LLM-Base+LLM-X+Alpaca,初期,LLM-Base为Chatglm6B底座模型,LLM-X是LLAMA增强模型。该方案简易高效,目标是使此类语言模型能够低能耗广泛部署,并最终在小模型的基座上发生“智能涌现”,力图最小计算代价达成ChatGPT、GPT4、ChatRWKV等人类友好亲和效果。当前可以满足总结、提问、问答、摘要、改写、评论、扮演等各种需求。
🔥🔥🔥A collection of some awesome public SNN(Spiking Neural Network) projects.
A paper list of spiking neural networks, including papers, codes, and related websites.
Leaky Integrate and Fire (LIF) model implementation for FPGA
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Implementation of the paper Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks
A supervised learning algorithm of SNN is proposed by using spike sequences with complex spatio-temporal information. We explore an error back-propagation method of SNN based on gradient descent. The chain rule proved mathematically that it is sufficient to update the SNN’s synaptic weights by directly using an optimizer. Utilizing the TensorFlow framework, a bilayer supervised learning SNN is constructed from scratch. We take the lead in the application of SAR image classification and conduct experiments on the MSTAR dataset.
Bio-inspired neuromorphic cerebellum
3D Spiking neural network simulation exploring Spike Timing Dependent Plasticity (STDP)
Python and ROS implementation of an SNN on Intel's Loihi neuromorphic processor mimicking the oculomotor system controlling a biomimetic robotic head
Showcases of Spiking Neural Network, which have Synaptic Plasticity
Self-Control Reservoir Network is a neural network concept that inspires from the human brain and from Reservoir Computing, designed for a better and smarter computing network
Bio-inspired spiking-neural-network framework on an autonomous robot car.
A demo for robotic control loop with Intel's Loihi neuromorphic chip used in our papers
Demo: Spiking Neural Network (SNN) using Generalised Linear Model (GLM)
A simple experiment to compare Artificial and Spiking Neural Networks in Sequential and Few-Shot Learning.
This repository contains all codes necessary to reproduce figures and results reported in Stein, Barbosa et al. (Nature Communications, 2020) from the raw data acquired in human behavioral experiments (data included in the repository), and from the relevant model simulations.
Network model of Rosenbaum et al. (2017) reimplemented in Brian 2. Developed as a course project during OCNC2017.
Simulation of a real time spiking neural network
Runs networkx graphs representing spiking neural networks of LIF-neurons on lava-nc or networkx.
code demos for primitives of spiking neural networks
Repo of the bachelor thesis 'Dynamic memory traces for sequence learning in spiking networks'
A neuroscientific sequence learning model on spiking neural networks with winner-take-all circuits and lateral inhibition. Written using the NEST neural simulator and custom neuron/synapse models.