boone891214

boone891214's Stars

• coulsonlee/NeurRev-ICLR2024

  Code for paper '' NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization '' in ICLR 2024

  2

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML10.8k934

• cool-xuan/Imbalanced_SAM

  The offical implement of ImbSAM (Imbalanced-SAM)

  Language:Python202

• princeton-nlp/LLM-Shearing

  [ICLR 2024] Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

  Language:Python54442

• coulsonlee/STDO-CVPR2023

  [CVPR2023] Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting

  Language:Python805

• he-y/Awesome-Pruning

  A curated list of neural network pruning resources.

  2.3k328

• VICO-UoE/DatasetCondensation

  Dataset Condensation (ICLR21 and ICML21)

  Language:Python47392

• Guang000/Awesome-Dataset-Distillation

  A curated list of awesome papers on dataset distillation and related applications.

  Language:HTML1.4k130

• OPTML-Group/BiP

  [NeurIPS22] "Advancing Model Pruning via Bi-level Optimization" by Yihua Zhang*, Yuguang Yao*, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, and Sijia Liu

  Language:Python14139

• GeorgeCazenavette/mtt-distillation

  Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

  Language:Python39254

• zejiangh/Filter-GaP

  The official PyTorch implementation of CHEX: CHannel EXploration for CNN Model Compression (CVPR 2022). Paper is available at https://openaccess.thecvf.com/content/CVPR2022/papers/Hou_CHEX_CHannel_EXploration_for_CNN_Model_Compression_CVPR_2022_paper.pdf

  Language:Jupyter Notebook378

• yenchenlin/nerf-pytorch

  A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

  Language:Python5.4k1.1k

• NVIDIA/DeepLearningExamples

  State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

  Language:Jupyter Notebook13.3k3.2k

• verbose-void/rigl-torch

  Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.

  Language:Jupyter Notebook556

• facebookresearch/deit

  Official DeiT repository

  Language:Python4k552

• facebookresearch/xcit

  Official code Cross-Covariance Image Transformer (XCiT)

  Language:Python65648

• raoyongming/DynamicViT

  [NeurIPS 2021] [T-PAMI] DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

  Language:Jupyter Notebook56470

• davda54/sam

  SAM: Sharpness-Aware Minimization (PyTorch)

  Language:Python1.7k197

• mtoneva/example_forgetting

  Language:Python17327

• divelab/DIG

  A library for graph deep learning research

  Language:Python1.9k281

• NazirNayal8/visual-transformer

  An implementation of the Visual Transformer Architecture introduced in the paper "Visual Transformers: Token-based Image Representation and Processing for Computer Vision" by Wu et al.

  Language:Jupyter Notebook173

• tahmid0007/VisualTransformers

  A Pytorch Implementation of the following paper "Visual Transformers: Token-based Image Representation and Processing for Computer Vision"

  Language:Python18129

• tomgoldstein/loss-landscape

  Code for visualizing the loss landscape of neural nets

  Language:Python2.8k395

• amirgholami/PyHessian

  PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

  Language:Jupyter Notebook676117

• timgaripov/dnn-mode-connectivity

  Mode Connectivity and Fast Geometric Ensembles in PyTorch

  Language:Python26544

• facebookresearch/pycls

  Codebase for Image Classification Research, written in PyTorch.

  Language:Python2.1k238

• jeonsworld/ViT-pytorch

  Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)

  Language:Jupyter Notebook1.9k363

• lucidrains/vit-pytorch

  Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

  Language:Python19.8k3k

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python31.7k4.7k

• acbull/LADIES

  Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"

  Language:Python7619