MAC-AutoML / OMPQLinks
☆25Updated 3 years ago
Alternatives and similar repositories for OMPQ
Users that are interested in OMPQ are comparing it to the libraries listed below
Sorting:
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆28Updated last year
- Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"☆62Updated 2 years ago
- [NeurIPS 2020] ShiftAddNet: A Hardware-Inspired Deep Network☆73Updated 4 years ago
- ☆17Updated 3 years ago
- ☆76Updated 3 years ago
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- ☆43Updated last year
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆34Updated last year
- The code for Joint Neural Architecture Search and Quantization☆13Updated 6 years ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆24Updated 4 years ago
- [ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binar…☆55Updated last year
- ☆17Updated 3 years ago
- [ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization☆94Updated 3 years ago
- BitSplit Post-trining Quantization☆50Updated 3 years ago
- [ICML 2022] ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks☆15Updated 3 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆33Updated 2 years ago
- PyTorch implementation of Towards Efficient Training for Neural Network Quantization☆15Updated 5 years ago
- Pytorch implementation of RAPQ, IJCAI 2022☆22Updated 2 years ago
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆30Updated last year
- Position-based Scaled Gradient for Model Quantization and Pruning Code (NeurIPS 2020)☆25Updated 4 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
- Code for ICML 2021 submission☆34Updated 4 years ago
- How Do Adam and Training Strategies Help BNNs Optimization? In ICML 2021.☆60Updated 4 years ago
- Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"☆20Updated 2 years ago
- [TMLR] Official PyTorch implementation of paper "Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precisio…☆46Updated last year
- Pytorch implementation of our paper (TNNLS) -- Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest Filters☆12Updated 3 years ago
- [ICML 2022] "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks", by Yonggan …☆72Updated 3 years ago
- Any-Precision Deep Neural Networks (AAAI 2021)☆61Updated 5 years ago
- [NeurIPS 2021] “Stronger NAS with Weaker Predictors“, Junru Wu, Xiyang Dai, Dongdong Chen, Yinpeng Chen, Mengchen Liu, Ye Yu, Zhangyang W…☆27Updated 3 years ago
- [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…☆77Updated 2 years ago