[CVPR 2023] DepGraph: Towards Any Structural Pruning
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Updated
Dec 8, 2024 - Python
[CVPR 2023] DepGraph: Towards Any Structural Pruning
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.
[TMLR 2024] Efficient Large Language Models: A Survey
Collection of recent methods on (deep) neural network compression and acceleration.
Efficient Deep Learning Systems course materials (HSE, YSDA)
Code and resources on scalable and efficient Graph Neural Networks
[CVPR 2024] Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
[NeurIPS2022] Official implementation of the paper 'Green Hierarchical Vision Transformer for Masked Image Modeling'.
[NeurIPS 2023] Structural Pruning for Diffusion Models
A list of papers, docs, codes about efficient AIGC. This repo is aimed to provide the info for efficient AIGC research, including language and vision, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
NeurIPS 2021, Official codes for "Efficient Training of Visual Transformers with Small Datasets".
Official implementation of "EAGLES: Efficient Accelerated 3D Gaussians with Lightweight EncodingS"
Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning
[ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.
[ICLR 2022] Data-Efficient Graph Grammar Learning for Molecular Generation
a curated list of high-quality papers on resource-efficient LLMs 🌱
The best collection of AI tutorials to make you a boss of Data Science!
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
📚 Collection of awesome generation acceleration resources.
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
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