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。
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Updated
Jun 3, 2024
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。
🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.
🔥🔥🔥A collection of some awesome public SNN(Spiking Neural Network) projects.
Self-Control Reservoir Network is a neural network concept that inspires from the human brain and from Reservoir Computing, designed for a better and smarter computing network
Code for VPRTempo, our temporally encoded spiking neural network for visual place recognition.
Offical implementation of "Spike-driven Transformer" (NeurIPS2023)
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
3D Spiking neural network simulation exploring Spike Timing Dependent Plasticity (STDP)
Implementation of the paper Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks
Runs networkx graphs representing spiking neural networks of LIF-neurons on lava-nc or networkx.
Leaky Integrate and Fire (LIF) model implementation for FPGA
Offical implementation of "Deep Directly-Trained Spiking Neural Networks for Object Detection" (ICCV2023)
Bio-inspired neuromorphic cerebellum
Cerebellum learning to perform the VOR.
Simulation of a real time spiking neural network
实现一种多Lora权值集成切换+Zero-Finetune零微调增强的跨模型技术方案,LLM-Base+LLM-X+Alpaca,初期,LLM-Base为Chatglm6B底座模型,LLM-X是LLAMA增强模型。该方案简易高效,目标是使此类语言模型能够低能耗广泛部署,并最终在小模型的基座上发生“智能涌现”,力图最小计算代价达成ChatGPT、GPT4、ChatRWKV等人类友好亲和效果。当前可以满足总结、提问、问答、摘要、改写、评论、扮演等各种需求。
Accelerated SNN simulator for neuromorphic computing and research in Python
Code and data to the publication "SpikE: spike-based embeddings for multi-relational graph data".
Mapping Spike Activities with Multiplicity, Adaptability, and Plasticity into Bio-Plausible Spiking Neural Networks
A neuroscientific sequence learning model on spiking neural networks with winner-take-all circuits and lateral inhibition. Written using the NEST neural simulator and custom neuron/synapse models.
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