Variational Dropout and the Local Reparameterization Trick

8 June 2015

Papers citing "Variational Dropout and the Local Reparameterization Trick"

36 / 236 papers shown

Title
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 18 482 0 14 Aug 2018
A Survey on Methods and Theories of Quantized Neural Networks Yunhui Guo MQ 27 230 0 13 Aug 2018
Understanding Dropout as an Optimization Trick Sangchul Hahn Heeyoul Choi ODL 13 34 0 26 Jun 2018
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 15 77 0 13 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 57 951 0 05 Jun 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 30 180 0 29 May 2018
Meta-Learning Probabilistic Inference For Prediction Jonathan Gordon J. Bronskill Matthias Bauer Sebastian Nowozin Richard E. Turner BDL 42 263 0 24 May 2018
Towards Robust Evaluations of Continual Learning Sebastian Farquhar Y. Gal CLL 28 305 0 24 May 2018
Excitation Dropout: Encouraging Plasticity in Deep Neural Networks Andrea Zunino Sarah Adel Bargal Pietro Morerio Jianming Zhang Stan Sclaroff Vittorio Murino 21 23 0 23 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 52 358 0 18 May 2018
Real-Time Prediction of the Duration of Distribution System Outages Aaron Jaech Baosen Zhang Mari Ostendorf D. Kirschen 11 74 0 03 Apr 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 19 432 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 9 307 0 12 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
Compressing Neural Networks using the Variational Information Bottleneck Bin Dai Chen Zhu David Wipf MLT 22 178 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 39 366 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 34 47 0 13 Feb 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 22 144 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 19 173 0 03 Nov 2017
Learning Discrete Weights Using the Local Reparameterization Trick Oran Shayer Dan Levi Ethan Fetaya 13 88 0 21 Oct 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 17 479 0 24 May 2017
Deep Relaxation: partial differential equations for optimizing deep neural networks Pratik Chaudhari Adam M. Oberman Stanley Osher Stefano Soatto G. Carlier 24 153 0 17 Apr 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 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 50 41 0 23 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 30 158 0 20 May 2016
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos Max Welling BDL 20 253 0 15 Mar 2016
Improved Dropout for Shallow and Deep Learning Zhe Li Boqing Gong Tianbao Yang BDL SyDa 27 79 0 06 Feb 2016
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks Chunyuan Li Changyou Chen David Carlson Lawrence Carin ODL BDL 27 319 0 23 Dec 2015
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks Y. Gal Zoubin Ghahramani UQCV DRL BDL 17 1,642 0 16 Dec 2015
Variational Auto-encoded Deep Gaussian Processes Zhenwen Dai Andreas C. Damianou Javier I. González Neil D. Lawrence BDL 18 130 0 19 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 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 7,634 0 03 Jul 2012