Fast Conditional Network Compression Using Bayesian HyperNetworks

13 May 2022

Dang Nguyen

Papers citing "Fast Conditional Network Compression Using Bayesian HyperNetworks"

23 / 23 papers shown

Title
Mathematical Models of Overparameterized Neural Networks Cong Fang Hanze Dong Tong Zhang 152 23 0 27 Dec 2020
Characterising Bias in Compressed Models Sara Hooker Nyalleng Moorosi Gregory Clark Samy Bengio Emily L. Denton 70 185 0 06 Oct 2020
Batch-Shaping for Learning Conditional Channel Gated Networks B. Bejnordi Tijmen Blankevoort Max Welling AI4CE 61 77 0 15 Jul 2019
CondConv: Conditionally Parameterized Convolutions for Efficient Inference Brandon Yang Gabriel Bender Quoc V. Le Jiquan Ngiam MedIm 3DV 72 636 0 10 Apr 2019
MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning Zechun Liu Haoyuan Mu Xiangyu Zhang Zichao Guo Xin Yang K. Cheng Jian Sun 80 563 0 25 Mar 2019
You Look Twice: GaterNet for Dynamic Filter Selection in CNNs Zhourong Chen Yang Li Samy Bengio Si Si 87 99 0 27 Nov 2018
HAQ: Hardware-Aware Automated Quantization with Mixed Precision Kuan-Chieh Wang Zhijian Liu Chengyue Wu Ji Lin Song Han MQ 129 884 0 21 Nov 2018
Fashionable Modelling with Flux Mike Innes Elliot Saba Keno Fischer Dhairya Gandhi Marco Concetto Rudilosso Neethu Mariya Joy Tejan Karmali Avik Pal Viral B. Shah AI4CE 76 164 0 01 Nov 2018
Dynamic Channel Pruning: Feature Boosting and Suppression Xitong Gao Yiren Zhao Łukasz Dudziak Robert D. Mullins Chengzhong Xu 76 318 0 12 Oct 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 48 78 0 13 Jun 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 159 3,138 0 15 Dec 2017
Learning Sparse Neural Networks through $L_0$ Regularization Christos Louizos Max Welling Diederik P. Kingma 433 1,147 0 04 Dec 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 125 1,825 0 16 Jun 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 166 481 0 24 May 2017
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Noam M. Shazeer Azalia Mirhoseini Krzysztof Maziarz Andy Davis Quoc V. Le Geoffrey E. Hinton J. Dean MoE 251 2,683 0 23 Jan 2017
Variational Dropout Sparsifies Deep Neural Networks Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov BDL 144 831 0 19 Jan 2017
HyperNetworks David R Ha Andrew M. Dai Quoc V. Le 164 1,632 0 27 Sep 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 287 4,807 0 04 Jan 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,854 0 01 Oct 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 226 1,518 0 08 Jun 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 332 18,647 0 06 Feb 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 384 3,151 0 15 Aug 2013