MingSun-Tse / TPP
[ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
☆32Updated last year
Alternatives and similar repositories for TPP:
Users that are interested in TPP are comparing it to the libraries listed below
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- ☆16Updated 2 years ago
- [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)☆83Updated 3 years ago
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆89Updated last year
- [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective☆36Updated 2 years ago
- In progress.☆63Updated 11 months ago
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆73Updated 2 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆30Updated 7 months ago
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆25Updated last year
- ☆30Updated 3 years ago
- ☆25Updated 3 years ago
- Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models☆34Updated last year
- [ICCV 2023] Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks☆23Updated last year
- [NeurIPS 2024] Search for Efficient LLMs☆12Updated 2 months ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆52Updated last year
- official implementation of Generative Low-bitwidth Data Free Quantization(GDFQ)☆53Updated last year
- ☆19Updated 2 years ago
- This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Qu…☆13Updated 2 years ago
- Pytorch implementation of our paper accepted by IEEE TNNLS, 2022 — Carrying out CNN Channel Pruning in a White Box☆18Updated 3 years ago
- ☆43Updated last year
- Pytorch implementation of our paper (TNNLS) -- Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters☆12Updated 3 years ago
- ☆26Updated 2 years ago
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆29Updated 3 years ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆25Updated 3 years ago
- Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization☆14Updated 2 years ago
- This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".☆41Updated 3 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- ☆10Updated 4 years ago
- ☆43Updated last year