这篇博客整理了从CVPR、ECCV、ICCV、AAAI到ICLR、ICML等会议中关于深度学习模型量化的重要论文，涵盖了2018年至2020年的时间段。重点探讨了量化技术在神经网络压缩、低比特运算、任务损失优化、硬件感知量化、权重和偏置校正、软量化、分层量化等多个方面，旨在实现高效且精确的整数运算 inference。
CVPR
2019
Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss
Quantization Networks
HAQ: Hardware-Aware Automated Quantization With Mixed Precision
2018
Two-Step Quantization for Low-Bit Neural Networks
Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation
Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Network
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