Pure python implementation of SNN

Deep learning with spiking neural networks (SNNs) in PyTorch.

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

Publicly available event datasets and transforms.

Code for "Convolutional spiking neural networks (SNN) for spatio-temporal feature extraction" paper

A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Documentation source for Lava

[IEEE TCYB 2023] The first large-scale tracking dataset by fusing RGB and Event cameras.

[CVPR'24 Spotlight] The official implementation of "State Space Models for Event Cameras"

Library for Drone Autonomy

PyTorch helper module to translate to and from NIR

Python tools to process and visualize address-event data from dynamic vision sensors such as DVS128

Multidigraph learning (MDGL) for training recurrent spiking neural networks

A series of simulation codes used to emulate quantum-like networks in the simulation of emergent adaptive behavior, such as network synchronization, and relate the nature of the coupled harmonic oscillators with non-local behavior and chimera states in systems of quantum particles. Coding Used is based on mathematical modelling of transport in q…

Simulation of Advanced Neuromorphic Architectures for Fast Exploration

ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.

Nengo extension to connect to FPGAs

a (simplistic) neuromimetic retina model based on open hardware such as the raspberry π