jaeho-lee / layer-adaptive-sparsityLinks
In progress.
☆64Updated last year
Alternatives and similar repositories for layer-adaptive-sparsity
Users that are interested in layer-adaptive-sparsity are comparing it to the libraries listed below
Sorting:
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated 2 years 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
- [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)☆83Updated 3 years ago
- ☆43Updated last year
- ☆25Updated 3 years ago
- This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".☆43Updated 3 years ago
- ☆12Updated last year
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆33Updated 3 years ago
- ☆45Updated last year
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆53Updated last year
- Pytorch implementation of our paper accepted by CVPR 2022 -- IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Sh…☆33Updated 3 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated last year
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆33Updated 10 months ago
- This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Qu…☆14Updated 2 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…☆90Updated last year
- Pytorch implementation of our paper accepted by ICCV 2021 -- ReCU: Reviving the Dead Weights in Binary Neural Networks http://arxiv.org/a…☆39Updated 3 years ago
- ☆17Updated 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
- Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"☆54Updated 2 years ago
- Recent Advances on Efficient Vision Transformers☆51Updated 2 years ago
- [ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan …☆71Updated 2 years ago
- Neuron Merging: Compensating for Pruned Neurons (NeurIPS 2020)☆43Updated 4 years ago
- An official implementation of "Network Quantization with Element-wise Gradient Scaling" (CVPR 2021) in PyTorch.☆94Updated last year
- Pytorch implementation of TPAMI 2022 -- 1xN Pattern for Pruning Convolutional Neural Networks☆43Updated 2 years ago
- ☆76Updated 2 years ago
- It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]☆29Updated 2 years ago
- ☆27Updated 2 years ago
- Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)☆26Updated 4 years ago
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆26Updated last year
- [ICCV 2023] Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks☆24Updated last year