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Search results for neuromorphic computing
neuromorphic-computing
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34 search results found
Micronet
⭐
2,177
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/in
Lava
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471
A Software Framework for Neuromorphic Computing
He4o
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316
HE —— “螺旋熵减机”
Neuromorphic Computing Guide
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191
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
Openeb
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142
Open source SDK to create applications leveraging event-based vision hardware equipment
Helix_theory
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132
theory of helix—— “螺旋论(可用来构建螺旋熵减机、及自然演化熵减机系统等)”
Spike Driven Transformer
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130
Offical implementation of "Spike-driven Transformer" (NeurIPS2023)
Lava Dl
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125
Deep Learning library for Lava
Dynex
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117
Dynex is a next-generation platform for neuromorphic computing based on a new flexible blockchain protocol. It consists of participating nodes that together constitute one enormous neuromorphic computing network. Consequently, the platform is capable of performing computations at unprecedented speeds and efficiency – even exceeding quantum computing. Everyone is welcome to participate, since the Dynex neuromorphic computing chip is capable of being simulated using almost any device, from regular
Open Neuromorphic
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114
List of open source neuromorphic projects: SNN training frameworks, DVS handling routines and so on.
Models
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69
This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.
Gac
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61
Offical implementation of "Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks" (AAAI2024)
Norse
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58
Deep learning for spiking neural networks
Lava Optimization
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47
Neuromorphic mathematical optimization with Lava
Awesome Spiking Neural Networks
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43
A paper list of spiking neural networks, including papers, codes, and related websites.
Lava Dnf
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39
Dynamic Neural Fields with Lava
Spiking Fullsubnet
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35
Official repository of Spiking-FullSubNet, the Intel N-DNS Challenge Algorithmic Track Winner.
Spikingformer
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27
Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network
Dynex Wallet App
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26
Dynex is a next-generation platform for neuromorphic computing based on a new flexible blockchain protocol.
Pyaer
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23
Low-level Python APIs for Accessing Neuromorphic Devices.
Spiking Neural Network On Fpga
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18
Leaky Integrate and Fire (LIF) model implementation for FPGA
Spiking Ddpg Mapless Navigation
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17
Spiking-DDPG trains an SNN for energy-efficient mapless navigation on Intel's Loihi neuromorphic processor.
Spikingformer Cml
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14
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Lsnn Official
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13
Long short-term memory Spiking Neural Networks
Pynmsnn
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11
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
Snn4space
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10
ANN to SNN conversion on land cover and land use classification problem for increased energy efficiency.
Dynex Neuromorphic Chip
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9
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.
Noisy Spiking Neuron Nets
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8
Official repo of Noisy Spiking Neural Networks
Spike
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8
Code and data to the publication "SpikE: spike-based embeddings for multi-relational graph data".
Memristor Models
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8
Python implementations and simulations of HP Labs Ion Drift and Yakopcic memristor models.
Dynex Whitepaper
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7
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.
Brain M
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6
Brilliantly Radical Artificially Intelligent Neural Machine
Event Based Velocity Prediction Snn
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5
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 i
Spiking Oculomotor Head Control
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5
Python and ROS implementation of an SNN on Intel's Loihi neuromorphic processor mimicking the oculomotor system controlling a biomimetic robotic head
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1-34 of 34 search results
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