MAC-AutoML / ITPruner
☆23Updated 3 years ago
Alternatives and similar repositories for ITPruner:
Users that are interested in ITPruner are comparing it to the libraries listed below
- ☆25Updated 3 years ago
- Code for ICCV23 paper "Automatic network pruning via Hilbert Schmidt independence criterion lasso under information bottleneck principle"☆17Updated last year
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆32Updated last year
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆24Updated 3 years ago
- ☆35Updated 2 years ago
- Pytorch implementation of our paper (TNNLS) -- Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters☆12Updated 2 years ago
- Pytorch implementation of our paper accepted by TPAMI 2023 — Lottery Jackpots Exist in Pre-trained Models☆32Updated last year
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆32Updated last year
- Pytorch implementation of our paper accepted by IEEE TNNLS, 2022 — Carrying out CNN Channel Pruning in a White Box☆18Updated 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
- Paper collection about model compression and acceleration: Pruning, Quantization, Knowledge Distillation, Low Rank Factorization, etc☆23Updated 4 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 TPAMI 2022 -- 1xN Pattern for Pruning Convolutional Neural Networks☆44Updated 2 years ago
- ☆16Updated 2 years ago
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆25Updated last year
- Pytorch implementation of our paper accepted by CVPR 2022 -- IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Sh…☆31Updated 2 years ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆30Updated 4 months ago
- XNAS: An effective, modular, and flexible Neural Architecture Search (NAS) framework.☆47Updated 2 years ago
- Official code of "NAS acceleration via proxy data", IJCAI21☆10Updated 2 years ago
- Code for our ICLR'2021 paper "DrNAS: Dirichlet Neural Architecture Search"☆44Updated 3 years ago
- [CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu…☆57Updated 3 years ago
- [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…☆27Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- [ICML 2022] ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks☆15Updated 2 years ago
- Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization☆14Updated 2 years ago
- 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
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated last year
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆50Updated last year
- Towards Compact CNNs via Collaborative Compression☆11Updated 2 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago