ESML

Event-based training of continuous time spiking networks in JAX

Event-based neural networks

Official implementation of our paper "Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models"

Building on our prior work on event-based state-space models, we developed an event-based state-space model based on the Mamba architecture for asynchronous streams of events such as event-based vision, spiking audio and point clouds.

This repository provides the code for the hands-on session of our tutorial on generalized neuromorphic neural architectures at the International Conference on Neuromorphic Systems (ICONS) 2024, Arlington, VA.

Easily create and optimize PyTorch networks as in the Deep Rewiring paper (https://igi-web.tugraz.at/PDF/241.pdf). Install using 'pip install deep_rewire'

Implementation of pure synaptic-delay training of spiking neural networks (based on SLAYER)