Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement
Learning

Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning

8 January 2019

Andreas Sedlmeier

Claudia Linnhoff-Popien

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Papers citing "Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning"

17 / 17 papers shown

Title
Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learning Daniel Flögel Marcos Gómez Villafane Joshua Ransiek Sören Hohmann 146 0 0 16 Sep 2024
Noise Contrastive Priors for Functional Uncertainty Danijar Hafner Dustin Tran Timothy Lillicrap A. Irpan James Davidson AAML BDL UQCV 115 74 0 24 Jul 2018
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 74 379 0 08 Jun 2018
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 168 2,072 0 08 Jun 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 179 592 0 22 May 2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery T. Schlegl Philipp Seeböck S. Waldstein U. Schmidt-Erfurth Georg Langs MedIm GAN 108 2,230 0 17 Mar 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 354 4,709 0 15 Mar 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 129 197 0 08 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 840 5,821 0 05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 164 3,454 0 07 Oct 2016
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 234 2,389 0 21 Jun 2016
Deep Exploration via Bootstrapped DQN Ian Osband Charles Blundell Alexander Pritzel Benjamin Van Roy 121 1,309 0 15 Feb 2016
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard Turner 114 140 0 10 Nov 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 829 9,318 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 187 1,887 0 20 May 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 130 946 0 18 Feb 2015
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 127 12,231 0 19 Dec 2013