Variational Dropout and the Local Reparameterization Trick

8 June 2015

Papers citing "Variational Dropout and the Local Reparameterization Trick"

38 / 288 papers shown

Title
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 26 6 0 19 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 60 358 0 18 May 2018
Real-Time Prediction of the Duration of Distribution System Outages Aaron Jaech Baosen Zhang Mari Ostendorf D. Kirschen 16 74 0 03 Apr 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 28 433 0 03 Apr 2018
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches Yeming Wen Paul Vicol Jimmy Ba Dustin Tran Roger C. Grosse BDL 22 307 0 12 Mar 2018
Variance Networks: When Expectation Does Not Meet Your Expectations Kirill Neklyudov Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov UQCV 18 23 0 10 Mar 2018
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning J. A. G. Higuera D. Meger Gregory Dudek BDL 22 39 0 06 Mar 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 30 898 0 28 Feb 2018
Compressing Neural Networks using the Variational Information Bottleneck Bin Dai Chen Zhu David Wipf MLT 26 178 0 28 Feb 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 41 365 0 26 Feb 2018
Bayesian Incremental Learning for Deep Neural Networks Max Kochurov T. Garipov D. Podoprikhin Dmitry Molchanov Arsenii Ashukha Dmitry Vetrov OOD CLL BDL 15 22 0 20 Feb 2018
Uncertainty Estimation via Stochastic Batch Normalization Andrei Atanov Arsenii Ashukha Dmitry Molchanov Kirill Neklyudov Dmitry Vetrov UQCV BDL 37 47 0 13 Feb 2018
Boundary Optimizing Network (BON) Marco Singh A. Pai 22 0 0 08 Jan 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 30 144 0 26 Dec 2017
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks Ziming Zhang M. Brand 26 70 0 20 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory Ron Amit Ron Meir BDL MLT 32 173 0 03 Nov 2017
Learning Discrete Weights Using the Local Reparameterization Trick Oran Shayer Dan Levi Ethan Fetaya 21 88 0 21 Oct 2017
Regularizing Deep Neural Networks by Noise: Its Interpretation and Optimization Hyeonwoo Noh Tackgeun You Jonghwan Mun Bohyung Han NoLa 29 197 0 14 Oct 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes Hugh Salimbeni M. Deisenroth BDL GP 39 415 0 24 May 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 23 479 0 24 May 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 45 585 0 22 May 2017
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution Ryutaro Tanno Daniel E. Worrall Aurobrata Ghosh Enrico Kaden S. Sotiropoulos A. Criminisi Daniel C. Alexander UQCV DiffM MedIm SupR 25 153 0 01 May 2017
Deep Relaxation: partial differential equations for optimizing deep neural networks Pratik Chaudhari Adam M. Oberman Stanley Osher Stefano Soatto G. Carlier 27 153 0 17 Apr 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 21 454 0 06 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Known Unknowns: Uncertainty Quality in Bayesian Neural Networks Ramon Oliveira Pedro Tabacof Eduardo Valle BDL UQCV 20 7 0 05 Dec 2016
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling Zhe Gan Chunyuan Li Changyou Chen Yunchen Pu Qinliang Su Lawrence Carin BDL UQCV 53 41 0 23 Nov 2016
Robustly representing uncertainty in deep neural networks through sampling Patrick McClure N. Kriegeskorte UQCV BDL OOD 31 15 0 05 Nov 2016
Regularization for Unsupervised Deep Neural Nets Baiyang Wang Diego Klabjan BDL 23 25 0 15 Aug 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 32 158 0 20 May 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 33 253 0 15 Mar 2016
Improved Dropout for Shallow and Deep Learning Zhe Li Boqing Gong Tianbao Yang BDL SyDa 30 79 0 06 Feb 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 27 320 0 23 Dec 2015
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks Y. Gal Zoubin Ghahramani UQCV DRL BDL 22 1,642 0 16 Dec 2015
Variational Auto-encoded Deep Gaussian Processes Zhenwen Dai Andreas C. Damianou Javier I. González Neil D. Lawrence BDL 24 131 0 19 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012