GATECH-EIC / Double-Win-QuantLinks
[ICML 2021] "Double-Win Quant: Aggressively Winning Robustness of Quantized DeepNeural Networks via Random Precision Training and Inference" by Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan Lin
☆16Updated 3 years ago
Alternatives and similar repositories for Double-Win-Quant
Users that are interested in Double-Win-Quant are comparing it to the libraries listed below
Sorting:
- Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples [NeurIPS 2021]☆33Updated 4 years ago
- ☆78Updated 3 years ago
- [ICLR 2021] HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark☆113Updated 2 years ago
- BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)☆42Updated 4 years ago
- ☆41Updated 3 years ago
- Any-Precision Deep Neural Networks (AAAI 2021)☆62Updated 5 years ago
- [NeurIPS 2020] "FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training" by Yonggan Fu, Ha…☆10Updated 3 years ago
- ☆21Updated 3 years ago
- [Neurips 2021] Sparse Training via Boosting Pruning Plasticity with Neuroregeneration☆31Updated 2 years ago
- ☆43Updated last year
- The official PyTorch implementation of the ICLR2022 paper, QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quan…☆127Updated 3 months ago
- ProxQuant: Quantized Neural Networks via Proximal Operators☆30Updated 6 years ago
- A collection of research papers on efficient training of DNNs☆70Updated 3 years ago
- code for the paper "A Statistical Framework for Low-bitwidth Training of Deep Neural Networks"☆29Updated 5 years ago
- The official implementation of TinyTrain [ICML '24]☆23Updated last year
- A pytorch implementation of DoReFa-Net☆132Updated 6 years ago
- Code needed to reproduce results from my ICLR 2019 paper on fixed-point quantization of the backprop algorithm.☆10Updated 6 years ago
- [IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.☆59Updated 2 years ago
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- This repo contains the code for studying the interplay between quantization and sparsity methods☆25Updated 10 months ago
- The PyTorch implementation of Learned Step size Quantization (LSQ) in ICLR2020 (unofficial)☆139Updated 5 years ago
- Pytorch implementation of our paper accepted by ICML 2023 -- "Bi-directional Masks for Efficient N:M Sparse Training"☆12Updated 2 years ago
- Code for ICML 2021 submission☆35Updated 4 years 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
- ☆19Updated 4 years ago
- This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".☆44Updated 4 years ago
- Reproducing Quantization paper PACT☆64Updated 3 years ago
- DNN quantization with outlier channel splitting (ICML'19)☆113Updated 5 years ago
- Official Implementation of Robustifying and Boosting Training-Free Neural Architecture Search☆10Updated last year
- Official implementation for ECCV 2022 paper LIMPQ - "Mixed-Precision Neural Network Quantization via Learned Layer-wise Importance"☆61Updated 2 years ago