Bayesian Compression for Deep Learning

24 May 2017

Papers citing "Bayesian Compression for Deep Learning"

50 / 68 papers shown

Title
Identifying Causal Direction via Variational Bayesian Compression Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen CML 34 0 0 12 May 2025
ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs Yuchen Yang Shubham Ugare Yifan Zhao Gagandeep Singh Sasa Misailovic MQ 26 0 0 31 Oct 2024
Neural Network Compression for Reinforcement Learning Tasks Dmitry A. Ivanov D. Larionov Oleg V. Maslennikov V. Voevodin OffRL AI4CE 45 0 0 13 May 2024
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design A. N. M. N. Abeer Sanket R. Jantre Nathan M. Urban Byung-Jun Yoon 44 1 0 30 Apr 2024
Pruning a neural network using Bayesian inference Sunil Mathew D. Rowe 10 0 0 04 Aug 2023
STen: Productive and Efficient Sparsity in PyTorch Andrei Ivanov Nikoli Dryden Tal Ben-Nun Saleh Ashkboos Torsten Hoefler 32 4 0 15 Apr 2023
SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report] Hamed Ayoobi Nico Potyka Francesca Toni 16 17 0 23 Jan 2023
CSQ: Growing Mixed-Precision Quantization Scheme with Bi-level Continuous Sparsification Lirui Xiao Huanrui Yang Zhen Dong Kurt Keutzer Li Du Shanghang Zhang MQ 27 10 0 06 Dec 2022
TEDL: A Two-stage Evidential Deep Learning Method for Classification Uncertainty Quantification Xue Li Wei Shen Denis Xavier Charles UQCV EDL 30 3 0 12 Sep 2022
Minimum Description Length Control Theodore H. Moskovitz Ta-Chu Kao M. Sahani M. Botvinick 20 1 0 17 Jul 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 65 75 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 40 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 30 6 0 13 May 2022
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity Arber Qoku Florian Buettner 21 5 0 13 Apr 2022
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification Sharath Girish Kamal Gupta Saurabh Singh Abhinav Shrivastava 28 11 0 06 Apr 2022
Nonlocal optimization of binary neural networks Amir Khoshaman Giuseppe Castiglione C. Srinivasa 13 0 0 05 Apr 2022
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes Hugh Dance Brooks Paige GP 20 10 0 08 Nov 2021
Neural network relief: a pruning algorithm based on neural activity Aleksandr Dekhovich David Tax M. Sluiter Miguel A. Bessa 46 10 0 22 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 30 43 0 01 Sep 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 32 1,109 0 07 Jul 2021
Learning Gradual Argumentation Frameworks using Genetic Algorithms J. Spieler Nico Potyka Steffen Staab AI4CE 31 4 0 25 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
COIN: COmpression with Implicit Neural representations Emilien Dupont Adam Goliñski Milad Alizadeh Yee Whye Teh Arnaud Doucet 20 223 0 03 Mar 2021
An Information-Theoretic Justification for Model Pruning Berivan Isik Tsachy Weissman Albert No 84 35 0 16 Feb 2021
Minimum Excess Risk in Bayesian Learning Aolin Xu Maxim Raginsky 26 37 0 29 Dec 2020
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and $L_0$ Regularization Yaniv Shulman 40 3 0 07 Dec 2020
Generalized Variational Continual Learning Noel Loo S. Swaroop Richard E. Turner BDL CLL 33 58 0 24 Nov 2020
Rethinking Weight Decay For Efficient Neural Network Pruning Hugo Tessier Vincent Gripon Mathieu Léonardon M. Arzel T. Hannagan David Bertrand 26 25 0 20 Nov 2020
Dirichlet Pruning for Neural Network Compression Kamil Adamczewski Mijung Park 27 3 0 10 Nov 2020
Neural Network Compression Via Sparse Optimization Tianyi Chen Bo Ji Yixin Shi Tianyu Ding Biyi Fang Sheng Yi Xiao Tu 36 15 0 10 Nov 2020
Training Sparse Neural Networks using Compressed Sensing Jonathan W. Siegel Jianhong Chen Pengchuan Zhang Jinchao Xu 24 5 0 21 Aug 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 17 20 0 16 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation Yoojin Choi Jihwan P. Choi Mostafa El-Khamy Jungwon Lee MQ 16 119 0 08 May 2020
Information-Theoretic Probing with Minimum Description Length Elena Voita Ivan Titov 19 270 0 27 Mar 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 17 326 0 22 Feb 2020
Iteratively Training Look-Up Tables for Network Quantization Fabien Cardinaux Stefan Uhlich K. Yoshiyama Javier Alonso García Lukas Mauch Stephen Tiedemann Thomas Kemp Akira Nakamura MQ 27 16 0 12 Nov 2019
Training DNN IoT Applications for Deployment On Analog NVM Crossbars F. García-Redondo Shidhartha Das G. Rosendale 17 5 0 30 Oct 2019
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks Simon Wiedemann H. Kirchhoffer Stefan Matlage Paul Haase Arturo Marbán ... Ahmed Osman D. Marpe H. Schwarz Thomas Wiegand Wojciech Samek 41 92 0 27 Jul 2019
Learning Multimodal Fixed-Point Weights using Gradient Descent Lukas Enderich Fabian Timm Lars Rosenbaum Wolfram Burgard MQ 17 9 0 16 Jul 2019
Sparse Networks from Scratch: Faster Training without Losing Performance Tim Dettmers Luke Zettlemoyer 20 333 0 10 Jul 2019
Deep Active Learning with Adaptive Acquisition Manuel Haussmann Fred Hamprecht M. Kandemir 16 41 0 27 Jun 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 23 77 0 19 Jun 2019
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers Igor Fedorov Ryan P. Adams Matthew Mattina P. Whatmough 13 164 0 28 May 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 32 14 0 27 May 2019
Training CNNs with Selective Allocation of Channels Jongheon Jeong Jinwoo Shin CVBM 31 15 0 11 May 2019
Towards Efficient Model Compression via Learned Global Ranking Ting-Wu Chin Ruizhou Ding Cha Zhang Diana Marculescu 16 170 0 28 Apr 2019
Where Do Human Heuristics Come From? Marcel Binz Dominik M. Endres 11 0 0 20 Feb 2019
Proximal Mean-field for Neural Network Quantization Thalaiyasingam Ajanthan P. Dokania Richard I. Hartley Philip H. S. Torr MQ 30 20 0 11 Dec 2018
Physics-informed deep generative models Yibo Yang P. Perdikaris AI4CE PINN 19 57 0 09 Dec 2018