Topic: neuromorphic-computing Goto Github
Some thing interesting about neuromorphic-computing
Some thing interesting about neuromorphic-computing
neuromorphic-computing,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
User: 666dzy666
neuromorphic-computing,Structured clustering for memristive crossbar based neuromorphic architectures
User: aayush-ankit
neuromorphic-computing,NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
User: ajayarunachalam
neuromorphic-computing,ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
User: andrzejkucik
neuromorphic-computing,Offical implementation of "Spike-driven Transformer" (NeurIPS2023)
User: biclab
Home Page: https://openreview.net/forum?id=9FmolyOHi5
neuromorphic-computing,Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)
User: biclab
Home Page: https://openreview.net/forum?id=1SIBN5Xyw7
neuromorphic-computing,Offical implementation of "Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks" (AAAI2024)
User: bollossom
Home Page: https://ojs.aaai.org/index.php/AAAI/article/view/27816
neuromorphic-computing,Public code for VTSNN: A Virtual Temporal Spiking Neural Network (Fron. Neur.)
User: bollossom
Home Page: https://www.frontiersin.org/articles/10.3389/fnins.2023.1091097/full
neuromorphic-computing,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.
Organization: cepdnaclk
Home Page: https://cepdnaclk.github.io/e16-4yp-neuromorphic-architecture/
neuromorphic-computing,PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Organization: combra-lab
neuromorphic-computing,Spiking-DDPG trains an SNN for energy-efficient mapless navigation on Intel's Loihi neuromorphic processor.
Organization: combra-lab
neuromorphic-computing,Python and ROS implementation of an SNN on Intel's Loihi neuromorphic processor mimicking the oculomotor system controlling a biomimetic robotic head
Organization: combra-lab
neuromorphic-computing,
Organization: cortical-team
neuromorphic-computing,Code and data to the publication "SpikE: spike-based embeddings for multi-relational graph data".
User: dodo47
Home Page: https://arxiv.org/abs/2104.13398
neuromorphic-computing,Low-level Python APIs for Accessing Neuromorphic Devices.
User: duguyue100
neuromorphic-computing,Dynex is the world’s only accessible neuromorphic quantum computing cloud for solving real-world problems, at scale.
User: dynexcoin
neuromorphic-computing,Dynex has also developed a proprietary circuit design, the Dynex Neuromorphic Chip, that complements the Dynex ecosystem and turns any modern G into a neuromorphic computing chip by simulating its equations of motion. This implementation proofs the mathematical model.
User: dynexcoin
neuromorphic-computing,With the end of Moore’s law approaching and Dennard scaling ending, the computing community is increasingly looking at new technologies to enable continued performance improvements. A neuromorphic computer is a nonvon Neumann computer whose structure and function are inspired by biology and physics. Today, such systems can be built and operated using existing technology, even at scale, and are capable of outperforming current quantum computers.
User: dynexcoin
neuromorphic-computing,Error Signals For Adaptive Neuro-Robotics: preliminary experiment
User: eladch
Home Page: http://nbel-lab.com/
neuromorphic-computing,Deep learning for spiking neural networks
Organization: electronicvisions
Home Page: https://norse.ai/docs
neuromorphic-computing,[CELL PATTERNS] Official repo of Noisy Spiking Neural Networks
User: genema
Home Page: https://cell.com/patterns/fulltext/S2666-3899(23)00200-3
neuromorphic-computing,Official repository of Spiking-FullSubNet, the Intel N-DNS Challenge Algorithmic Track Winner.
User: haoxiangsnr
Home Page: https://haoxiangsnr.github.io/spiking-fullsubnet/
neuromorphic-computing,Event based aperture robust flow
User: himstien
neuromorphic-computing,This repository contains the tutorials and homework assignments for CSCE 790: Neuromorphic computing course at UofSC.
Organization: icas-lab
Home Page: https://www.icaslab.com/teaching/csce790nc
neuromorphic-computing,Long short-term memory Spiking Neural Networks
Organization: igitugraz
neuromorphic-computing,This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.
Organization: intel-nrc-ecosystem
Home Page: http://neuromorphic.intel.com
neuromorphic-computing,Automatic differentiable design of photonic tensor cores
User: jeremiemelo
neuromorphic-computing,螺旋熵减系统
User: jiaxiaogang
Home Page: https://jiaxiaogang.github.io/
neuromorphic-computing,螺旋熵减理论
User: jiaxiaogang
Home Page: http://jiaxiaogang.github.io/
neuromorphic-computing,A mixing of neuromorphic and quantum computing for the Comparative Machine Learning class
User: johnberroa
neuromorphic-computing,A manifesto for temporal computing where memory indexing is replaced by temporal delays and referencing.
User: keskival
neuromorphic-computing,A Software Framework for Neuromorphic Computing
Organization: lava-nc
Home Page: https://lava-nc.org
neuromorphic-computing,Deep Learning library for Lava
Organization: lava-nc
Home Page: https://lava-nc.org
neuromorphic-computing,Dynamic Neural Fields with Lava
Organization: lava-nc
neuromorphic-computing,Neuromorphic mathematical optimization with Lava
Organization: lava-nc
Home Page: https://lava-nc.org/optimization.html
neuromorphic-computing,A Liquid State Machine using quantized neurons that are operating on lower-bit representations and fixed point computations. It provides a next step towards the implementation of efficient accelerators that can be used in the field of neuromorphic computing.
User: m4urin
neuromorphic-computing,Brilliantly Radical Artificially Intelligent Neural Machine
User: merterm
neuromorphic-computing,Leaky Integrate and Fire (LIF) model implementation for FPGA
User: metr0jw
neuromorphic-computing,Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
User: mikeroyal
neuromorphic-computing,An exploration of blind source audio separation using spiking neural networks. Latency, power. and intelligibility are primary objectives while bio-plausibility is left as a secondary objective to be addressed in the future.
User: neurosumbad
neuromorphic-computing,List of open source neuromorphic projects: SNN training frameworks, DVS handling routines and so on.
Organization: open-neuromorphic
neuromorphic-computing,This repository contains my current doctoral research at the University of Manchester
User: pabogdan
neuromorphic-computing,Open source SDK to create applications leveraging event-based vision hardware equipment
Organization: prophesee-ai
Home Page: https://www.prophesee.ai/metavision-intelligence/
neuromorphic-computing, 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)
User: shilpakancharla
neuromorphic-computing,Bio-inspired neuromorphic cerebellum
Organization: spinnakermanchester
neuromorphic-computing,Python implementations and simulations of HP Labs Ion Drift and Yakopcic memristor models.
User: thomastiotto
neuromorphic-computing,Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023
User: windere
neuromorphic-computing,A paper list of spiking neural networks, including papers, codes, and related websites.
User: zhouchenlin2096
neuromorphic-computing,Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network
User: zhouchenlin2096
neuromorphic-computing,Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
User: zhouchenlin2096
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