Variational Dropout and the Local Reparameterization Trick

8 June 2015

Papers citing "Variational Dropout and the Local Reparameterization Trick"

50 / 225 papers shown

Title
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
Adaptive Regularization via Residual Smoothing in Deep Learning Optimization Jung-Kyun Cho Junseok Kwon Byung-Woo Hong 26 1 0 23 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 27 141 0 17 Jul 2019
Supervised Uncertainty Quantification for Segmentation with Multiple Annotations Shi Hu Daniel E. Worrall Stefan Knegt Bastiaan S. Veeling Henkjan Huisman Max Welling UQCV 9 94 0 03 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 21 77 0 19 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 24 8 0 10 Jun 2019
Practical Deep Learning with Bayesian Principles Kazuki Osawa S. Swaroop Anirudh Jain Runa Eschenhagen Richard E. Turner Rio Yokota Mohammad Emtiyaz Khan BDL UQCV 44 240 0 06 Jun 2019
Non-linear Multitask Learning with Deep Gaussian Processes Ayman Boustati Theodoros Damoulas R. Savage BDL 9 5 0 29 May 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 29 14 0 27 May 2019
Decentralized Bayesian Learning over Graphs Anusha Lalitha Xinghan Wang O. Kilinc Y. Lu T. Javidi F. Koushanfar FedML 28 25 0 24 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 29 8 0 23 May 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 13 149 0 25 Apr 2019
Relational Reasoning Network (RRN) for Anatomical Landmarking N. Torosdagli Syed Muhammad Anwar P. Verma D. Liberton Janice S. Lee Wade W. Han Ulas Bagci 17 3 0 08 Apr 2019
Effective and Efficient Dropout for Deep Convolutional Neural Networks Shaofeng Cai Jinyang Gao Gang Chen Beng Chin Ooi Wei Wang Meihui Zhang BDL 13 53 0 06 Apr 2019
Progressive Stochastic Binarization of Deep Networks David Hartmann Michael Wand MQ 12 1 0 03 Apr 2019
Correlated Parameters to Accurately Measure Uncertainty in Deep Neural Networks K. Posch J. Pilz UQCV BDL 9 28 0 02 Apr 2019
Focused Quantization for Sparse CNNs Yiren Zhao Xitong Gao Daniel Bates Robert D. Mullins Chengzhong Xu MQ 15 26 0 07 Mar 2019
Variational Inference to Measure Model Uncertainty in Deep Neural Networks K. Posch J. Steinbrener J. Pilz UQCV BDL 12 27 0 26 Feb 2019
Task2Vec: Task Embedding for Meta-Learning Alessandro Achille Michael Lam Rahul Tewari Avinash Ravichandran Subhransu Maji Charless C. Fowlkes Stefano Soatto Pietro Perona SSL 12 309 0 10 Feb 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 28 854 0 18 Jan 2019
Guided Dropout Rohit Keshari Richa Singh Mayank Vatsa BDL 18 37 0 10 Dec 2018
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 19 52 0 03 Dec 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 31 220 0 30 Nov 2018
Structured Pruning of Neural Networks with Budget-Aware Regularization Carl Lemaire Andrew Achkar Pierre-Marc Jodoin 22 92 0 23 Nov 2018
Sequential Neural Methods for Likelihood-free Inference Conor Durkan George Papamakarios Iain Murray BDL 33 24 0 21 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 28 392 0 19 Nov 2018
A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks Alberto Marchisio Muhammad Abdullah Hanif Semeen Rehman Maurizio Martina Muhammad Shafique 13 11 0 27 Oct 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Metropolis-Hastings view on variational inference and adversarial training Kirill Neklyudov Evgenii Egorov Pavel Shvechikov Dmitry Vetrov GAN 26 13 0 16 Oct 2018
Rethinking the Value of Network Pruning Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang Trevor Darrell 8 1,449 0 11 Oct 2018
Deterministic Variational Inference for Robust Bayesian Neural Networks Anqi Wu Sebastian Nowozin Edward Meeds Richard E. Turner José Miguel Hernández-Lobato Alexander L. Gaunt UQCV AAML BDL 29 16 0 09 Oct 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network Xuanqing Liu Yao Li Chongruo Wu Cho-Jui Hsieh AAML OOD 16 171 0 01 Oct 2018
Switching Isotropic and Directional Exploration with Parameter Space Noise in Deep Reinforcement Learning Izumi Karino Kazutoshi Tanaka Ryuma Niiyama Y. Kuniyoshi 9 3 0 18 Sep 2018
Extracting representations of cognition across neuroimaging studies improves brain decoding A. Mensch Julien Mairal B. Thirion Gaël Varoquaux AI4CE 16 15 0 17 Sep 2018
Probabilistic Binary Neural Networks Jorn W. T. Peters Max Welling BDL UQCV MQ 17 50 0 10 Sep 2018
A Neural Temporal Model for Human Motion Prediction Anand Gopalakrishnan A. Mali Daniel Kifer C. Lee Giles Alexander Ororbia 3DH 23 173 0 09 Sep 2018
Pyramidal Recurrent Unit for Language Modeling Sachin Mehta Rik Koncel-Kedziorski Mohammad Rastegari Hannaneh Hajishirzi 19 10 0 27 Aug 2018
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 39 951 0 05 Jun 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 27 180 0 29 May 2018
Meta-Learning Probabilistic Inference For Prediction Jonathan Gordon J. Bronskill Matthias Bauer Sebastian Nowozin Richard E. Turner BDL 39 263 0 24 May 2018
Towards Robust Evaluations of Continual Learning Sebastian Farquhar Y. Gal CLL 16 304 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 43 358 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