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Projects in Awesome Lists tagged with neuromorphic-computing

A curated list of projects in awesome lists tagged with neuromorphic-computing .

https://github.com/666DZY666/micronet

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

batch-normalization-fuse bnn convolutional-networks dorefa group-convolution integer-arithmetic-only model-compression network-in-network network-slimming neuromorphic-computing onnx post-training-quantization pruning pytorch quantization quantization-aware-training tensorrt tensorrt-int8-python twn xnor-net

Last synced: 20 Mar 2025

https://github.com/lava-nc/lava

A Software Framework for Neuromorphic Computing

deep-learning neural-networks neuromorphic neuromorphic-computing neuroscience python

Last synced: 14 May 2025

https://github.com/BICLab/Spike-Driven-Transformer

Offical implementation of "Spike-driven Transformer" (NeurIPS2023)

neuromorphic-computing spike-driven spiking-neural-network spiking-transformer transformer-based-snn

Last synced: 21 Apr 2025

https://github.com/htm-community/htm.core

Actively developed Hierarchical Temporal Memory (HTM) community fork (continuation) of NuPIC. Implementation for C++ and Python

ai anomaly-detection cortical-learning cpp hierarchical-temporal-memory htm neural-networks neuromorphic-computing neuroscience neuroscience-inspired-ai nupic prediction reproducible-research sparse-distributed-memory

Last synced: 09 Jul 2025

https://github.com/BICLab/Spike-Driven-Transformer-V2

Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)

neuromorphic-computing neuromorphic-hardware spiking-neural-networks

Last synced: 21 Apr 2025

https://github.com/igitugraz/lsnn-official

Long short-term memory Spiking Neural Networks

machine-learning neuromorphic-computing spiking-neural-networks

Last synced: 14 Apr 2025

https://github.com/BICLab/SpikeYOLO

Offical implementation of "Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection" (ECCV2024 Oral)

neuromorphic-computing spiking-neural-networks

Last synced: 04 Sep 2025

https://github.com/duguyue100/pyaer

Low-level Python APIs for Accessing Neuromorphic Devices.

amd64 arm64 event-camera neuromorphic-computing neuromorphic-engineering numpy python swig zmq

Last synced: 16 Aug 2025

https://github.com/shilpakancharla/event-based-velocity-prediction-snn

Neuromorphic computing uses very-large-scale integration (VLSI) systems with the goal of replicating neurobiological structures and signal conductance mechanisms. Neuromorphic processors can run spiking neural networks (SNNs) that mimic how biological neurons function, particularly by emulating the emission of electrical spikes. A key benefit of using SNNs and neuromorphic technology is the ability to optimize the size, weight, and power consumed in a system. SNNs can be trained and employed in various robotic and computer vision applications; we attempt to use event-based to create a novel approach in order to the predict velocity of objects moving in frame. Data generated in this work is recorded and simulated as event camera data using ESIM. Vicon motion tracking data provides the ground truth position and time values, from which the velocity is calculated. The SNNs developed in this work regress the velocity vector, consisting of the x, y, and z-components, while using the event data, or the list of events associated with each velocity measurement, as the input features. With the use of the novel dataset created, three SNN models were trained and then the model that minimized the loss function the most was further validated by omitting a subset of data used in the original training. The average loss, in terms of RMSE, on the test set after using the trained model on the omitted subset of data was 0.000386. Through this work, it is shown that it is possible to train an SNN on event data in order to predict the velocity of an object in view. (Spring 2022 MS Computer Science Thesis - North Carolina State University)

event-camera neuromorphic-computing regression-models spiking-neural-networks

Last synced: 14 May 2025

https://github.com/cepdnaclk/e16-4yp-neuromorphic-architecture

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, as the first stage, we are implementing parallel multiple processing elements based on RISC-V architecture to represent biological neurons. Single neurons can be implemented as a single processor with local memory access or since the spike time of biological neurons is in the millisecond order multiple neurons can be virtualized to a single processor. At the second stage of the process, we are expecting to design encoders and decoders to benchmark the architecture by solving classical machine learning problems.

fpga neuromorphic-computing neuromorphic-engineering neuromorphic-hardware risc-v

Last synced: 06 Feb 2026

https://github.com/anulum/sc-neurocore

Universal Stochastic Computing Framework for Neuromorphic Hardware — Rust SIMD engine, Python simulation, Verilog RTL, HDC/VSA, SCPN integration

edge-ai fpga hyper-dimensional-computing neuromorphic neuromorphic-computing petri-nets pyo3 quantum rust simd snn spiking-neural-networks stochastic-computing verilog

Last synced: 02 Apr 2026

https://github.com/igitugraz/se-adlif

Code for "Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation"

neuromorphic-computing neuroscience oscillations spiking-neural-networks

Last synced: 14 Apr 2025

https://github.com/johnberroa/Duel-of-the-Numbers

A mixing of neuromorphic and quantum computing for the Comparative Machine Learning class

game neuromorphic-computing quantum-computing

Last synced: 14 Mar 2025

https://github.com/johnberroa/duel-of-the-numbers

A mixing of neuromorphic and quantum computing for the Comparative Machine Learning class

game neuromorphic-computing quantum-computing

Last synced: 12 Apr 2025

https://github.com/lava-nc/lava-docs

Documentation source for Lava

neuromorphic neuromorphic-computing

Last synced: 12 Apr 2025

https://github.com/matthewfilipovich/neural-network-pde-solver

Partial Differential Equation (PDE) solver using neural networks with the Nengo package.

nengo neural-network neuromorphic-computing pde-solver

Last synced: 05 Jul 2025

https://github.com/pabogdan/neurogenesis

This repository contains my current doctoral research at the University of Manchester

neuromorphic-computing pynn spinnaker structural-plasticity synaptic-plasticity theoretical-neuroscience

Last synced: 03 Mar 2025

https://github.com/eladch/error-signals-for-adaptive-neuro-robotics

Error Signals For Adaptive Neuro-Robotics: preliminary experiment

neuromorphic-computing neuromorphic-engineering pid-controller

Last synced: 06 Apr 2025

https://github.com/dylanperdigao/bayesian-optimization-1d-csnn

Source code of the paper entitled "Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks through Bayesian Optimization", and presented at EPIA 2024, the 23rd International Conference on Artificial Intelligence.

1d-convolution bayesian-optimization epia2024 fairness fraud-detection neuromorphic-computing snntorch spiking-neural-networks

Last synced: 11 Mar 2026

https://github.com/thennen/stochasticsynapses.jl

Fast model for large arrays of solid-state stochastic synapses

emerging-technology gpu julia machine-learning neuromorphic-computing reram stochastic-model synapse

Last synced: 04 Feb 2026

https://github.com/russelljjarvis/genn_on_jetson

A Basic Guide for configuring the Nvidia Jetson Nano for running the GENN Potjan et al cortical models developed by Knight et al.

accessibility neuromorphic-computing neuron-simulations

Last synced: 19 Mar 2026

https://github.com/galihru/neuromorphicrecognitioncomputing

Implements a biologically-inspired SNN architecture for real-time processing.

facial-expression-recognition neuromorphic-computing python3 realtime-framework snn

Last synced: 28 Jul 2025

https://github.com/bringhurst/snnd

Spiking Neural Network Daemon

neuromorphic-computing spiking-neural-networks

Last synced: 04 Sep 2025

https://github.com/or4k2l/robust-vision

Production-ready framework for training robust computer vision models. Features multi-GPU support, EMA tracking, label smoothing, and comprehensive robustness evaluation across 4 noise types. Includes scalable TF.Data pipeline, automated testing, Docker support, and CLI tools. Install: pip install robust-vision

autonomous-driving computer-vision confidence-estimation deep-learning docker hardware-aware-ml implicit-regularization jax kitti-dataset machine-learning memristive-crossbar multi-gpu neuromorphic-computing neuromorphic-hardware noise-robustness pattern-recognition production-ml python robust-ml

Last synced: 22 Feb 2026