Concrete Dropout

22 May 2017

Alex Kendall

Papers citing "Concrete Dropout"

33 / 133 papers shown

Title
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control Rhiannon Michelmore Matthew Wicker Luca Laurenti L. Cardelli Y. Gal Marta Z. Kwiatkowska BDL 8 105 0 21 Sep 2019
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors Jayaraman J. Thiagarajan Bindya Venkatesh P. Sattigeri P. Bremer UQCV 25 31 0 09 Sep 2019
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels Felix J. S. Bragman Ryutaro Tanno Sebastien Ourselin Daniel C. Alexander M. Jorge Cardoso 24 86 0 26 Aug 2019
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation Amir Atapour-Abarghouei Stephen Bonner A. Mcgough 24 7 0 19 Aug 2019
Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations Andras Rozsa Terrance E. Boult AAML 24 18 0 07 Aug 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 31 289 0 16 Jul 2019
Variational Inference MPC for Bayesian Model-based Reinforcement Learning Masashi Okada T. Taniguchi 38 73 0 08 Jul 2019
MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation Lorenzo Bertoni S. Kreiss Alexandre Alahi UQCV 33 117 0 14 Jun 2019
Perceptual Attention-based Predictive Control Keuntaek Lee G. N. An Viacheslav Zakharov Evangelos A. Theodorou 15 19 0 26 Apr 2019
Survey of Dropout Methods for Deep Neural Networks Alex Labach Hojjat Salehinejad S. Valaee 27 149 0 25 Apr 2019
Centerline Depth World Reinforcement Learning-based Left Atrial Appendage Orifice Localization Walid Abdullah Al I. Yun E. Chun 16 1 0 02 Apr 2019
The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction Ruihan Hu Qijun Huang Sheng Chang Hao Wang Jin He UQCV 14 32 0 25 Feb 2019
Multi-modal Ensemble Classification for Generalized Zero Shot Learning Rafael Felix Michele Sasdelli Ian Reid G. Carneiro VLM 21 20 0 15 Jan 2019
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien UQCV 20 24 0 08 Jan 2019
Guided Dropout Rohit Keshari Richa Singh Mayank Vatsa BDL 26 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 24 52 0 03 Dec 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 33 220 0 30 Nov 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 396 0 19 Nov 2018
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 24 397 0 21 Sep 2018
Accurate Uncertainties for Deep Learning Using Calibrated Regression Volodymyr Kuleshov Nathan Fenner Stefano Ermon BDL UQCV 27 622 0 01 Jul 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 21 372 0 08 Jun 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
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes Tongfei Chen Jirí Navrátil Vijay Iyengar Karthikeyan Shanmugam 10 42 0 14 May 2018
Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection Di Feng Lars Rosenbaum Klaus C. J. Dietmayer 3DPC UQCV 22 242 0 13 Apr 2018
Safe end-to-end imitation learning for model predictive control Keuntaek Lee Kamil Saigol Evangelos A. Theodorou BDL 24 24 0 27 Mar 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 52 358 0 22 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
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 27 52 0 13 Feb 2018
DropoutDAgger: A Bayesian Approach to Safe Imitation Learning Kunal Menda Katherine Driggs-Campbell Mykel J. Kochenderfer 24 28 0 18 Sep 2017
Deep and Confident Prediction for Time Series at Uber Lingxue Zhu N. Laptev BDL AI4TS 30 342 0 06 Sep 2017
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