A simple approach for quantizing neural networks

7 September 2022

Papers citing "A simple approach for quantizing neural networks"

6 / 6 papers shown

Title
Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging Ismail Erbas Vikas Pandey Aporva Amarnath Naigang Wang Karthik Swaminathan Stefan T. Radev Xavier Intes AI4CE 19 1 0 01 Oct 2024
Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization Holger Boche Vít Fojtík Adalbert Fono Gitta Kutyniok 35 0 0 12 Aug 2024
MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization Aozhong Zhang Naigang Wang Yanxia Deng Xin Li Zi Yang Penghang Yin MQ 37 4 0 02 Jun 2024
Frame Quantization of Neural Networks Wojciech Czaja Sanghoon Na 19 1 0 11 Apr 2024
SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization Jinjie Zhang Rayan Saab 13 0 0 20 Sep 2023
Tuning-free one-bit covariance estimation using data-driven dithering S. Dirksen J. Maly 23 7 0 24 Jul 2023