Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

6 June 2015

Papers citing "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

50 / 1,180 papers shown

Title
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 11 66 0 09 Aug 2018
Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy Firat Özdemir Z. Peng C. Tanner Philipp Fürnstahl O. Goksel 17 28 0 18 Jul 2018
Practical Obstacles to Deploying Active Learning David Lowell Zachary Chase Lipton Byron C. Wallace 25 111 0 12 Jul 2018
Machine Learning in High Energy Physics Community White Paper K. Albertsson Piero Altoe D. Anderson John R. Anderson Michael Andrews ... Michael Williams Wenjing Wu Stefan Wunsch Kun Yang O. Zapata AI4CE 6 220 0 08 Jul 2018
A survey on policy search algorithms for learning robot controllers in a handful of trials Konstantinos Chatzilygeroudis Vassilis Vassiliades F. Stulp Sylvain Calinon Jean-Baptiste Mouret 17 154 0 06 Jul 2018
Simpler but More Accurate Semantic Dependency Parsing Timothy Dozat Christopher D. Manning GNN 13 177 0 03 Jul 2018
Dropout-based Active Learning for Regression Evgenii Tsymbalov Maxim Panov Alexander Shapeev BDL UQCV 6 56 0 26 Jun 2018
Understanding Dropout as an Optimization Trick Sangchul Hahn Heeyoul Choi ODL 13 34 0 26 Jun 2018
On the Implicit Bias of Dropout Poorya Mianjy R. Arora René Vidal 17 66 0 26 Jun 2018
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions Zach Eaton-Rosen Felix J. S. Bragman Sotirios Bisdas Sebastien Ourselin M. Jorge Cardoso UQCV 23 85 0 22 Jun 2018
Bayesian Prediction of Future Street Scenes through Importance Sampling based Optimization Apratim Bhattacharyya Mario Fritz Bernt Schiele UQCV BDL 14 2 0 18 Jun 2018
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning Felix J. S. Bragman Ryutaro Tanno Zach Eaton-Rosen Wenqi Li D. Hawkes Sebastien Ourselin Daniel C. Alexander J. McClelland M. Jorge Cardoso UQCV 17 49 0 18 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
Meta-Learning for Stochastic Gradient MCMC Wenbo Gong Yingzhen Li José Miguel Hernández-Lobato BDL 16 44 0 12 Jun 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 12 373 0 08 Jun 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 17 68 0 06 Jun 2018
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images S. Graham Hao Chen Jevgenij Gamper Qi Dou Pheng-Ann Heng David R. J. Snead Yee Wah Tsang Nasir M. Rajpoot MedIm 19 301 0 05 Jun 2018
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 29 951 0 05 Jun 2018
Learn the new, keep the old: Extending pretrained models with new anatomy and images Firat Özdemir Philipp Fürnstahl Orçun Göksel CLL 27 48 0 01 Jun 2018
Short-term Load Forecasting with Deep Residual Networks Kunjin Chen Kunlong Chen Qin Wang Ziyu He Jun Hu Jinliang He 27 463 0 30 May 2018
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 19 464 0 30 May 2018
Lightweight Probabilistic Deep Networks Jochen Gast Stefan Roth UQCV OOD BDL 25 180 0 29 May 2018
Towards Robust Evaluations of Continual Learning Sebastian Farquhar Y. Gal CLL 13 304 0 24 May 2018
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers Yonatan Geifman Guy Uziel Ran El-Yaniv UQCV 17 132 0 21 May 2018
SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning W. Wen Yandan Wang Feng Yan Cong Xu Chunpeng Wu Yiran Chen H. Li 21 50 0 21 May 2018
Nonparametric Bayesian Deep Networks with Local Competition Konstantinos P. Panousis S. Chatzis Sergios Theodoridis BDL 9 32 0 19 May 2018
Mad Max: Affine Spline Insights into Deep Learning Randall Balestriero Richard Baraniuk AI4CE 23 78 0 17 May 2018
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes Tongfei Chen Jirí Navrátil Vijay Iyengar Karthikeyan Shanmugam 6 42 0 14 May 2018
Confidence Modeling for Neural Semantic Parsing Li Dong Chris Quirk Mirella Lapata 11 82 0 11 May 2018
SHADE: Information Based Regularization for Deep Learning Michael Blot Thomas Robert Nicolas Thome Matthieu Cord 10 12 0 29 Apr 2018
FPR -- Fast Path Risk Algorithm to Evaluate Collision Probability A. Blake Alejandro Bordallo Kamen Brestnichki Majd Hawasly Svetlin Penkov S. Ramamoorthy Alexandre Silva 18 6 0 15 Apr 2018
Safe end-to-end imitation learning for model predictive control Keuntaek Lee Kamil Saigol Evangelos A. Theodorou BDL 11 24 0 27 Mar 2018
Calibrated Prediction Intervals for Neural Network Regressors Gil Keren N. Cummins Björn Schuller UQCV 17 31 0 26 Mar 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 9 358 0 22 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick D. McDaniel OOD AAML 6 502 0 13 Mar 2018
Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey Muzammal Naseer Salman H Khan Fatih Porikli 3DPC 3DV 11 100 0 09 Mar 2018
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning J. A. G. Higuera D. Meger Gregory Dudek BDL 20 39 0 06 Mar 2018
Deep Network Regularization via Bayesian Inference of Synaptic Connectivity Harris Partaourides S. Chatzis BDL 20 4 0 04 Mar 2018
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C. Riquelme George Tucker Jasper Snoek BDL 27 366 0 26 Feb 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks Mattias Teye Hossein Azizpour Kevin Smith BDL UQCV 20 239 0 18 Feb 2018
Uncertainty Estimation via Stochastic Batch Normalization Andrei Atanov Arsenii Ashukha Dmitry Molchanov Kirill Neklyudov Dmitry Vetrov UQCV BDL 24 47 0 13 Feb 2018
Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning T. Vandal E. Kodra Jennifer Dy S. Ganguly R. Nemani A. Ganguly UQCV BDL 19 52 0 13 Feb 2018
Curriculum Learning by Transfer Learning: Theory and Experiments with Deep Networks D. Weinshall Gad Cohen Dan Amir ODL 17 239 0 11 Feb 2018
Information Planning for Text Data Vadim Smolyakov 14 0 0 09 Feb 2018
Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty Apratim Bhattacharyya Mario Fritz Bernt Schiele 21 201 0 24 Nov 2017
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security Hao Dong Chao Wu Zhen Wei Yike Guo 30 30 0 20 Nov 2017
Active Learning for Visual Question Answering: An Empirical Study Xiaoyu Lin Devi Parikh 36 31 0 06 Nov 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 19 1,068 0 01 Nov 2017
Dropout Sampling for Robust Object Detection in Open-Set Conditions Dimity Miller Lachlan Nicholson Feras Dayoub Niko Sünderhauf BDL UQCV 31 233 0 18 Oct 2017
Learning a Predictive Model for Music Using PULSE Jonas Langhabel 6 1 0 26 Sep 2017