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Bayesian Compression for Deep Learning

24 May 2017

Papers citing "Bayesian Compression for Deep Learning"

50 / 269 papers shown

Title
Masked Bayesian Neural Networks : Computation and Optimality Insung Kong Dongyoon Yang Jongjin Lee Ilsang Ohn Yongdai Kim TPM 58 1 0 02 Jun 2022
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems Hongpeng Zhou W. Pan 39 4 0 01 Jun 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 128 78 0 28 May 2022
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility Hoileong Lee Fadhel Ayed Paul Jung Juho Lee Hongseok Yang François Caron 104 10 0 17 May 2022
Fast Conditional Network Compression Using Bayesian HyperNetworks Phuoc Nguyen T. Tran Ky Le Sunil R. Gupta Santu Rana Dang Nguyen Trong Nguyen S. Ryan Svetha Venkatesh BDL 54 7 0 13 May 2022
Robust Learning of Parsimonious Deep Neural Networks Valentin Frank Ingmar Guenter Athanasios Sideris 75 2 0 10 May 2022
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity Arber Qoku Florian Buettner 86 5 0 13 Apr 2022
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification Sharath Girish Kamal Gupta Saurabh Singh Abhinav Shrivastava 98 11 0 06 Apr 2022
Nonlocal optimization of binary neural networks Amir Khoshaman Giuseppe Castiglione C. Srinivasa 57 0 0 05 Apr 2022
Interpretable Latent Variables in Deep State Space Models Haoxuan Wu David S. Matteson M. Wells BDL AI4TS 72 0 0 03 Mar 2022
Towards Effective and Robust Neural Trojan Defenses via Input Filtering Kien Do Haripriya Harikumar Hung Le D. Nguyen T. Tran Santu Rana Dang Nguyen Willy Susilo Svetha Venkatesh AAML 68 13 0 24 Feb 2022
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning Meet P. Vadera Adam D. Cobb Brian Jalaian Benjamin M. Marlin BDL 48 2 0 08 Feb 2022
Cyclical Pruning for Sparse Neural Networks Suraj Srinivas Andrey Kuzmin Markus Nagel M. V. Baalen Andrii Skliar Tijmen Blankevoort 96 13 0 02 Feb 2022
Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks Runpei Dong Zhanhong Tan Mengdi Wu Linfeng Zhang Kaisheng Ma MQ 94 12 0 30 Dec 2021
A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks via Learned Weights Statistics Prasen Kumar Sharma Arun Abraham V. N. Rajendiran MQ 109 8 0 06 Dec 2021
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems Meet P. Vadera Benjamin M. Marlin UQCV BDL 51 5 0 03 Dec 2021
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes Hugh Dance Brooks Paige GP 74 10 0 08 Nov 2021
Analysis of memory consumption by neural networks based on hyperparameters N. Mahendran 36 2 0 21 Oct 2021
Mining the Weights Knowledge for Optimizing Neural Network Structures Mengqiao Han Xiabi Liu Zhaoyang Hai Xin Duan 27 1 0 11 Oct 2021
Neural network relief: a pruning algorithm based on neural activity Aleksandr Dekhovich David Tax M. Sluiter Miguel A. Bessa 120 11 0 22 Sep 2021
$On the Compression of Neural Networks Using $\ell_0$-Norm Regularization and Weight Pruning$ On the Compression of Neural Networks Using $\ell_0$ -Norm Regularization and Weight Pruning F. Oliveira E. Batista R. Seara 75 10 0 10 Sep 2021
Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation Andreas Voskou Konstantinos P. Panousis D. Kosmopoulos Dimitris N. Metaxas S. Chatzis SLR 97 43 0 01 Sep 2021
Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details Sanket Jantre Shrijita Bhattacharya T. Maiti BDL 88 14 0 25 Aug 2021
A fast asynchronous MCMC sampler for sparse Bayesian inference Yves F. Atchadé Liwei Wang 53 3 0 14 Aug 2021
Only Train Once: A One-Shot Neural Network Training And Pruning Framework Tianyi Chen Bo Ji Tianyu Ding Biyi Fang Guanyi Wang Zhihui Zhu Luming Liang Yixin Shi Sheng Yi Xiao Tu 136 105 0 15 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 242 1,179 0 07 Jul 2021
Partition and Code: learning how to compress graphs Giorgos Bouritsas Andreas Loukas Nikolaos Karalias M. Bronstein 85 13 0 05 Jul 2021
Learning Gradual Argumentation Frameworks using Genetic Algorithms J. Spieler Nico Potyka Steffen Staab AI4CE 70 4 0 25 Jun 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights H. Ritter Martin Kukla Chen Zhang Yingzhen Li UQCV BDL 94 17 0 30 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 141 134 0 14 May 2021
Efficacy of Bayesian Neural Networks in Active Learning Vineeth Rakesh Swayambhoo Jain BDL 46 10 0 02 Apr 2021
Cascade Weight Shedding in Deep Neural Networks: Benefits and Pitfalls for Network Pruning K. Azarian Fatih Porikli CVBM 48 0 0 19 Mar 2021
COIN: COmpression with Implicit Neural representations Emilien Dupont Adam Goliñski Milad Alizadeh Yee Whye Teh Arnaud Doucet 123 228 0 03 Mar 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 91 30 0 25 Feb 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 167 37 0 16 Feb 2021
Structured Dropout Variational Inference for Bayesian Neural Networks S. Nguyen Duong Nguyen Khai Nguyen Khoat Than Hung Bui Nhat Ho BDL DRL 70 8 0 16 Feb 2021
Neural Network Compression for Noisy Storage Devices Berivan Isik Kristy Choi Xin-Yang Zheng Tsachy Weissman Stefano Ermon H. P. Wong Armin Alaghi 70 13 0 15 Feb 2021
Variational Bayesian Sequence-to-Sequence Networks for Memory-Efficient Sign Language Translation Harris Partaourides Andreas Voskou D. Kosmopoulos S. Chatzis Dimitris N. Metaxas SLR 44 4 0 11 Feb 2021
Deep Model Compression based on the Training History S. H. Shabbeer Basha M. Farazuddin Viswanath Pulabaigari S. Dubey Snehasis Mukherjee VLM 83 18 0 30 Jan 2021
Variational Nested Dropout Yufei Cui Yushun Mao Ziquan Liu Qiao Li Antoni B. Chan Xue Liu Tei-Wei Kuo Chun Jason Xue BDL 61 5 0 27 Jan 2021
Overfitting for Fun and Profit: Instance-Adaptive Data Compression T. V. Rozendaal Iris A. M. Huijben Taco S. Cohen 105 47 0 21 Jan 2021
Single-path Bit Sharing for Automatic Loss-aware Model Compression Jing Liu Bohan Zhuang Peng Chen Chunhua Shen Jianfei Cai Mingkui Tan MQ 58 8 0 13 Jan 2021
Minimum Excess Risk in Bayesian Learning Aolin Xu Maxim Raginsky 427 40 0 29 Dec 2020
Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization Joshua C. Chang P. Fletcher Ju Han Ted L.Chang Shashaank Vattikuti Bart Desmet Ayah Zirikly Carson C. Chow 56 4 0 08 Dec 2020
The Role of Regularization in Shaping Weight and Node Pruning Dependency and Dynamics Yael Ben-Guigui Jacob Goldberger Tammy Riklin-Raviv 50 0 0 07 Dec 2020
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization Yaniv Shulman 94 3 0 07 Dec 2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization Kien Do T. Tran Svetha Venkatesh BDL 53 3 0 03 Dec 2020
Generalized Variational Continual Learning Noel Loo S. Swaroop Richard Turner BDL CLL 93 60 0 24 Nov 2020
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 112 26 0 20 Nov 2020
TreeGen -- a Monte Carlo generator for data frames A. Niemczynowicz Gabriela Bialoskórska Joanna Niezurawska-Zajac Radosław Antoni Kycia 11 0 0 17 Nov 2020