Low-Precision Stochastic Gradient Langevin Dynamics

20 June 2022

Papers citing "Low-Precision Stochastic Gradient Langevin Dynamics"

37 / 37 papers shown

Title
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks Martin Ferianc Partha P. Maji Matthew Mattina Miguel R. D. Rodrigues UQCV BDL 54 9 0 22 Feb 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions Wei Deng Guang Lin F. Liang BDL 54 28 0 19 Oct 2020
Training Binary Neural Networks using the Bayesian Learning Rule Xiangming Meng Roman Bachmann Mohammad Emtiyaz Khan BDL MQ 59 42 0 25 Feb 2020
Sampling-Free Learning of Bayesian Quantized Neural Networks Jiahao Su Milan Cvitkovic Furong Huang BDL MQ UQCV 39 7 0 06 Dec 2019
Computational Separations between Sampling and Optimization Kunal Talwar 42 12 0 05 Nov 2019
QPyTorch: A Low-Precision Arithmetic Simulation Framework Tianyi Zhang Zhiqiu Lin Guandao Yang Christopher De Sa MQ 45 66 0 09 Oct 2019
Bayesian Inference for Large Scale Image Classification Jonathan Heek Nal Kalchbrenner UQCV BDL 91 33 0 09 Aug 2019
SWALP : Stochastic Weight Averaging in Low-Precision Training Guandao Yang Tianyi Zhang Polina Kirichenko Junwen Bai A. Wilson Christopher De Sa 51 97 0 26 Apr 2019
Learned Step Size Quantization S. K. Esser J. McKinstry Deepika Bablani R. Appuswamy D. Modha MQ 69 798 0 21 Feb 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 72 275 0 11 Feb 2019
Training Deep Neural Networks with 8-bit Floating Point Numbers Naigang Wang Jungwook Choi D. Brand Chia-Yu Chen K. Gopalakrishnan MQ 58 500 0 19 Dec 2018
Sampling Can Be Faster Than Optimization Yian Ma Yuansi Chen Chi Jin Nicolas Flammarion Michael I. Jordan 65 184 0 20 Nov 2018
Adversarial Distillation of Bayesian Neural Network Posteriors Kuan-Chieh Wang Paul Vicol James Lucas Li Gu Roger C. Grosse R. Zemel UQCV GAN AAML BDL 47 56 0 27 Jun 2018
Quantizing deep convolutional networks for efficient inference: A whitepaper Raghuraman Krishnamoorthi MQ 127 1,013 0 21 Jun 2018
Binary Ensemble Neural Network: More Bits per Network or More Networks per Bit? Shilin Zhu Xin Dong Hao Su MQ 66 137 0 20 Jun 2018
Scalable Methods for 8-bit Training of Neural Networks Ron Banner Itay Hubara Elad Hoffer Daniel Soudry MQ 84 337 0 25 May 2018
Training and Inference with Integers in Deep Neural Networks Shuang Wu Guoqi Li F. Chen Luping Shi MQ 57 390 0 13 Feb 2018
VIBNN: Hardware Acceleration of Bayesian Neural Networks R. Cai Ao Ren Ning Liu Caiwen Ding Luhao Wang Xuehai Qian Massoud Pedram Yanzhi Wang BDL 73 87 0 02 Feb 2018
Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference Benoit Jacob S. Kligys Bo Chen Menglong Zhu Matthew Tang Andrew G. Howard Hartwig Adam Dmitry Kalenichenko MQ 136 3,111 0 15 Dec 2017
Mixed Precision Training Paulius Micikevicius Sharan Narang Jonah Alben G. Diamos Erich Elsen ... Boris Ginsburg Michael Houston Oleksii Kuchaiev Ganesh Venkatesh Hao Wu 149 1,792 0 10 Oct 2017
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 65 296 0 29 Sep 2017
Computation Error Analysis of Block Floating Point Arithmetic Oriented Convolution Neural Network Accelerator Design Zhourui Song Zhenyu Liu Dongsheng Wang 45 42 0 22 Sep 2017
Control Variates for Stochastic Gradient MCMC Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 49 101 0 16 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 262 5,812 0 14 Jun 2017
Training Quantized Nets: A Deeper Understanding Hao Li Soham De Zheng Xu Christoph Studer H. Samet Tom Goldstein MQ 53 210 0 07 Jun 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 83 41 0 23 Nov 2016
Stochastic Gradient MCMC with Stale Gradients Changyou Chen Nan Ding Chunyuan Li Yizhe Zhang Lawrence Carin BDL 62 23 0 21 Oct 2016
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients Shuchang Zhou Yuxin Wu Zekun Ni Xinyu Zhou He Wen Yuheng Zou MQ 112 2,085 0 20 Jun 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.0K 193,426 0 10 Dec 2015
Fixed Point Quantization of Deep Convolutional Networks D. Lin S. Talathi V. Annapureddy MQ 90 814 0 19 Nov 2015
BinaryConnect: Training Deep Neural Networks with binary weights during propagations Matthieu Courbariaux Yoshua Bengio J. David MQ 192 2,984 0 02 Nov 2015
A Complete Recipe for Stochastic Gradient MCMC Yian Ma Tianqi Chen E. Fox BDL SyDa 60 486 0 15 Jun 2015
Bayesian Dark Knowledge Masashi Sugiyama Vivek Rathod R. Garnett Max Welling BDL UQCV 74 258 0 14 Jun 2015
Training Binary Multilayer Neural Networks for Image Classification using Expectation Backpropagation Zhiyong Cheng Daniel Soudry Zexi Mao Zhenzhong Lan MQ 67 52 0 12 Mar 2015
Deep Learning with Limited Numerical Precision Suyog Gupta A. Agrawal K. Gopalakrishnan P. Narayanan HAI 176 2,046 0 09 Feb 2015
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 104 908 0 17 Feb 2014
MCMC using Hamiltonian dynamics Radford M. Neal 290 3,276 0 09 Jun 2012