Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks

20 May 2016

Papers citing "Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks"

9 / 9 papers shown

Title
AutoQNN: An End-to-End Framework for Automatically Quantizing Neural Networks Cheng Gong Ye Lu Surong Dai Deng Qian Chenkun Du Tao Li MQ 21 0 0 07 Apr 2023
AdaPT: Fast Emulation of Approximate DNN Accelerators in PyTorch Dimitrios Danopoulos Georgios Zervakis K. Siozios Dimitrios Soudris J. Henkel 14 31 0 08 Mar 2022
GDRQ: Group-based Distribution Reshaping for Quantization Haibao Yu Tuopu Wen Guangliang Cheng Jiankai Sun Qi Han Jianping Shi MQ 11 3 0 05 Aug 2019
Optimally Scheduling CNN Convolutions for Efficient Memory Access Arthur Stoutchinin Francesco Conti Luca Benini 17 43 0 04 Feb 2019
Deep Positron: A Deep Neural Network Using the Posit Number System Zachariah Carmichael Seyed Hamed Fatemi Langroudi Char Khazanov Jeffrey Lillie J. Gustafson Dhireesha Kudithipudi MQ 4 96 0 05 Dec 2018
QUENN: QUantization Engine for low-power Neural Networks Miguel de Prado Maurizio Denna Luca Benini Nuria Pazos MQ 19 14 0 14 Nov 2018
Quantization for Rapid Deployment of Deep Neural Networks J. Lee Sangwon Ha Saerom Choi Won-Jo Lee Seungwon Lee MQ 6 48 0 12 Oct 2018
Minimum Energy Quantized Neural Networks Bert Moons Koen Goetschalckx Nick Van Berckelaer Marian Verhelst MQ 17 123 0 01 Nov 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 15 479 0 24 May 2017