Pure python implementation of SNN
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Updated
Jul 29, 2022 - Python
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
[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).
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.
ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
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…
Metrics for spiking neural networks based on torchmetrics
Bio-inspired neuromorphic cerebellum
Multidigraph learning (MDGL) for training recurrent spiking neural networks
Library for Drone Autonomy
[CCS'22] Backdoor Attacks on Spiking NNs and Neuromorphic Datasets
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
Coding projects by the community for the community
Learning how to use the Akida neuromorphic processor with a Camera feed
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