Pure python implementation of SNN

Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.

Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)

RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.

OpenN@S: Open-source software to NAS automatic VHDL code generation

Brilliantly Radical Artificially Intelligent Neural Machine

NeMo - A hardware agnostic neuromorphic processor simulation model built on ROSS

An Address Event Representation toolbox for loading and visualising event data files in Python

Bio-inspired neuromorphic cerebellum

Neuromorphic Auditory Visualizer Tool

openFrameworks addon for interfacing to the Dynamic Vision Sensors. This addon is a basic logger and player for the DAVIS/DVS sensors family

Neuromorphic architectures are hardware architectures that use the biologically inspired neural functions as the basis of operation. Information processing based on spiking neuron architectures have caught considerable attention in recent years due to its low power consumption compared to traditional artificial neural networks. In this project, …

E-prop on spinnaker 2: exploring online learning in spiking rnns on neuromorphic hardware

Simulation of Advanced Neuromorphic Architectures for Fast Exploration

A fast generative model for stochastic memory cells

A human-machine created programming language for neuromorphic engineering.

A flexible package manager designed to support multiple versions, configurations, platforms, and compilers.

This is a collection of papers I read on SNN accelerators.