A simple approach for quantizing neural networks

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A simple approach for quantizing neural networks

Applied and Computational Harmonic Analysis (ACHA), 2022

7 September 2022

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Papers citing "A simple approach for quantizing neural networks"

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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 135 1 0 01 Oct 2024
Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through QuantizationJournal of Fourier Analysis and Applications (JFAA), 2024 Holger Boche Vít Fojtík Adalbert Fono Gitta Kutyniok 314 1 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 199 15 0 02 Jun 2024
Frame Quantization of Neural Networks Wojciech Czaja Sanghoon Na 166 1 0 11 Apr 2024
SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization Jinjie Zhang Rayan Saab 159 0 0 20 Sep 2023
Tuning-free one-bit covariance estimation using data-driven ditheringIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023 S. Dirksen J. Maly 453 9 0 24 Jul 2023