Qianpeng Li's repositories
Neuromorphic-Processor-paper-list
I will share some useful or interesting papers about neuromorphic processor
Awesome-Spiking-Neural-Networks
Awesome Spiking Neural Networks
dataset-for-snn
some datasets for snn
awesome-model-quantization
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
Awesome-Pruning
A curated list of neural network pruning resources.
Blender_Neural_Network
Create an artificial neural network in Blender
ccf-deadlines
⏰ CCF recommendation conference Deadline Countdowns / Please star this project, thanks~
Compiler
Machine learning compiler based on MLIR for Sophgo TPU.
dvs128_gesture_pytorch
Original DVS128 Gesture Dataset in PyTorch
Efficient-spiking-networks
Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT
first-contributions
🚀✨ Help beginners to contribute to open source projects
micrograd
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Neural-Networks-on-Silicon
This is originally a collection of papers on neural network accelerators. Now it's more like my selection of research on deep learning and computer architecture.
QianpengLi577
Config files for my GitHub profile.
Re-Loss
Reducing Information Loss for Spiking Neural Networks
SNN_arxiv_daily
this repository cord my subscriptions in arxiv with spiking neural network, and [this](https://github.com/shenhaibo123/SNN_summaries) is my summaries.
spikformer
ICLR 2023, Spikformer: When Spiking Neural Network Meets Transformer
STBP-Explicit-Progressive-Propagation-Process
STBP 梯度显式计算过程，只包括最后一层的计算过程，其他层计算过程随后补充
tangent
Source-to-Source Debuggable Derivatives in Pure Python
tiny-gpu
A minimal GPU design in Verilog to learn how GPUs work from the ground up