Pure python implementation of SNN
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Updated
Jul 29, 2022 - Python
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
Simulation of Advanced Neuromorphic Architectures for Fast Exploration
A human-AI developed programming language for Neuromorphic Engineering
Bio-inspired neuromorphic cerebellum
Neuromorphic Auditory Visualizer Tool
An Address Event Representation toolbox for loading and visualising event data files in Python
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, …
A fast generative model for stochastic memory cells
E-prop on spinnaker 2: exploring online learning in spiking rnns on neuromorphic hardware
A flexible package manager designed to support multiple versions, configurations, platforms, and compilers.
This is a collection of papers I read on SNN accelerators.
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