Quantized Neural Networks for Low-Precision Accumulation with Guaranteed Overflow Avoidance

31 January 2023

Papers citing "Quantized Neural Networks for Low-Precision Accumulation with Guaranteed Overflow Avoidance"

6 / 6 papers shown

Title
Mixed precision accumulation for neural network inference guided by componentwise forward error analysis El-Mehdi El Arar Silviu-Ioan Filip Theo Mary Elisa Riccietti 52 0 0 19 Mar 2025
Accumulator-Aware Post-Training Quantization Ian Colbert Fabian Grob Giuseppe Franco Jinjie Zhang Rayan Saab MQ 22 3 0 25 Sep 2024
An Energy-Efficient Edge Computing Paradigm for Convolution-based Image Upsampling Ian Colbert Ken Kreutz-Delgado Srinjoy Das 38 4 0 15 Jul 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 195 5,175 0 16 Sep 2016