Simulation of spiking neural networks (SNNs) using PyTorch.

Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration

spiking-neural-networks

This is a repository with implementations of neuron models, synapses, and spiking neural networks (SNN). It's still in development and it has original content in terms of code.

Repository for the master thesis titled "Local Unsupervised Learning of Multimodal Event-Based Data with Spiking Neural Networks", by Julian Lopez Gordillo (MSc in Artificial Intelligence, 2019-2021).

Nuerapse simulations for SNNs

Convolutional spiking neural network implementing STDP

A generalizable model of spike-timing dependent plasticity for the Neural Simulation Tool (NEST).

Convolutional spiking neural network implementing voltage-dependent synaptic plasticity and single-spike integrate-and-fire neurons

Spiking neural networks are biologically plausible CNNs which learn through a temporally dependent learning method known as Spike Time Dependant Plasticity (STDP)- an alternate to gradient descent. This repository contains layers built on top of Lasagne layers for spiking neural networks. This is the first implementation of spiking neural networ…

STDP implementation for Nengo and single layer network

Convolutional Spiking Neural Network to recognize speech utterances using Spike-Timing-Dependent Plasticity

Implementation of Spiking Neural Networks (SNNs) using SpykeTorch, featuring STDP and R-STDP training methods for efficient neural computation.

Malleable spiking neural network framework and training platform.

Probably the world most FC implementation of transformers with SNNs

CPU-based spiking neural network framework for classification layers employing first-spike coding and supervised STDP training.

[TMLR] S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks

A simple experiment to compare Artificial and Spiking Neural Networks in Sequential and Few-Shot Learning.

A Python toolkit for advanced mathematics in AI and computational neuroscience, designed to support the development of the Fully Unified Model (FUM).

SNN MNIST "Unsupervised learning of digit recognition using spike-timing-dependent plasticity"