[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
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Updated
Jul 22, 2024 - Python
[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
Code and resources on scalable and efficient Graph Neural Networks
NeurIPS 2021, Official codes for "Efficient Training of Visual Transformers with Small Datasets".
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
[NeurIPS 2023] Structural Pruning for Diffusion Models
[ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
This repository provides implementation of a baseline method and our proposed methods for efficient Skeleton-based Human Action Recognition.
[NeurIPS2022] Official implementation of the paper 'Green Hierarchical Vision Transformer for Masked Image Modeling'.
Pytorch implementation for stereo matching described in the paper: Efficient Deep learning for stereo matching
Efficient Deep Learning for Stereo Matching Tensorflow 2.x
Frame Flexible Network (CVPR2023)
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
[ICML 2023] Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction
[NeurIPS 2019 Google MicroNet Challenge] MSUNet is an efficient model that won the 4th place in the Google MicroNet Challenge CIFAR-100 Track hosted at NeurIPS 2019 designed by Yu Zheng, Shen Yan, Mi Zhang
[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
Code repository of the paper "Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups" https://proceedings.mlr.press/v162/knigge22a.html
[ICLR 2022] "Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently", by Xiaohan Chen, Jason Zhang and Zhangyang Wang.
Official PyTorch training code of Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity (ICCV2023-RCV)
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