guoyufei's repositories
Awesome-Spiking-Neural-Networks
Awesome Spiking Neural Networks
Ternary-Spike
Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks
Real-Spike
Real Spike: Learning Real-valued Spikes for Spiking Neural Networks
Joint-A-SNN
Joint A-SNN: Joint Training of Artificial and Spiking Neural Networks via Self-Distillation and Weight Factorization
meshsmoothing
some mesh smoothing methods
IM-Loss-Information-Maximization-Loss-for-Spiking-Neural-Networks
Official simplified implementation of IM-Loss.
yfguo91.github.io
AcadHomepage: A Modern and Responsive Academic Personal Homepage
3D-Machine-Learning
A resource repository for 3D machine learning
awesome-scientific-computing
:sunglasses: Curated list of awesome software for numerical analysis and scientific computing
benchmark_results
Visual Tracking Paper List
open_clip
An open source implementation of CLIP.
pcl
Point Cloud Library (PCL)
Pointnet_Pointnet2_pytorch
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
PyTorch-Spiking-YOLOv3
A minimal PyTorch implementation of Spiking-YOLOv3, based on the minimal PyTorch implementation of PyTorch-YOLOv3(eriklindernoren/PyTorch-YOLOv3), with support for spiking-yolov3-tiny at present.
pytorch_image_classification
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
remesher
Isotropic surface remeshing software
RepDistiller
[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods
Solving_ImageNet
Official PyTorch implementation of the paper: "Solving ImageNet: a Unified Scheme for Training any Backbone to Top Results" (2022)
Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
super-gradients
Easily train or fine-tune SOTA computer vision models with one open source training library