PyTorch implementation of DynapSE neural model
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Updated
Sep 24, 2024 - Python
PyTorch implementation of DynapSE neural model
Deep learning with spiking neural networks (SNNs) in PyTorch.
Coding projects by the community for the community
PyTorch helper module to translate to and from NIR
Publicly available event datasets and transforms.
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
Simulation of Advanced Neuromorphic Architectures for Fast Exploration
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…
[IEEE TCYB 2023] The first large-scale tracking dataset by fusing RGB and Event cameras.
Official PyTorch implementation of the CVPR 2024 paper: State Space Models for Event Cameras (Spotlight).
An open-source package that offer fully-functional spike-based bio-inspired hippocampal memory models implemented with SNN technology in the SpiNNaker hardware in Python
Visual Oscillators
Neuromorphic spatio-temporal receptive fields
Learning how to use the Akida neuromorphic processor with a Camera feed
Neurocam is a cutting-edge surveillance system for the Raspberry Pi 4 powered by the Akida neuromorphic processor with ChatGPT 4 frame analysis
Low-Power Image Classification on Neuromorphic Hardware
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