There are 10 repositories under neuromorphic-computing topic.
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
螺旋熵减系统
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" (NeurIPS2023)
A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊论文和代码,正在持续更新中。
List of open source neuromorphic projects: SNN training frameworks, DVS handling routines and so on.
Open source SDK to create applications leveraging event-based vision hardware equipment
Actively developed Hierarchical Temporal Memory (HTM) community fork (continuation) of NuPIC. Implementation for C++ and Python
Dynex is the world’s only accessible neuromorphic quantum computing cloud for solving real-world problems, at scale.
螺旋熵减理论
Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)
Long short-term memory Spiking Neural Networks
Offical implementation of "Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks" (AAAI2024)
This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.
Spiking-DDPG trains an SNN for energy-efficient mapless navigation on Intel's Loihi neuromorphic processor.
Deep learning for spiking neural networks
Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network
Neuromorphic mathematical optimization with Lava
Official repository of Spiking-FullSubNet, the Intel N-DNS Challenge Algorithmic Track Winner.
Leaky Integrate and Fire (LIF) model implementation for FPGA
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware
Low-level Python APIs for Accessing Neuromorphic Devices.
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
Python implementations and simulations of HP Labs Ion Drift and Yakopcic memristor models.
[CELL PATTERNS] Official repo of Noisy Spiking Neural Networks
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.
Offical implementation of "Adaptive Smoothing Gradient Learning for Spiking Neural Networks", ICML 2023
Structured clustering for memristive crossbar based neuromorphic architectures
Code and data to the publication "SpikE: spike-based embeddings for multi-relational graph data".