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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

5 December 2016

Balaji Lakshminarayanan

Alexander Pritzel

Papers citing "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles"

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Title
Calibration of Encoder Decoder Models for Neural Machine Translation Aviral Kumar Sunita Sarawagi 207 100 0 03 Mar 2019
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation Geoffrey C. Fox J. Glazier J. Kadupitiya V. Jadhao Minje Kim ... Madhav Marathe Abhijin Adiga Jiangzhuo Chen O. Beckstein S. Jha 53 53 0 27 Feb 2019
The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction Ruihan Hu Qijun Huang Sheng Chang Hao Wang Jin He UQCV 66 32 0 25 Feb 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 175 200 0 19 Feb 2019
Detecting and Diagnosing Incipient Building Faults Using Uncertainty Information from Deep Neural Networks Baihong Jin Dan Li S. Srinivasan See-Kiong Ng K. Poolla Alberto L. Sangiovanni-Vincentelli UQCV AI4CE 33 26 0 18 Feb 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 88 278 0 11 Feb 2019
A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans Onur Ozdemir Rebecca L. Russell A. Berlin 53 170 0 08 Feb 2019
Evaluating Crowd Density Estimators via Their Uncertainty Bounds Jennifer Vandoni Emanuel Aldea S. L. Hégarat-Mascle UQCV 36 6 0 07 Feb 2019
Hybrid Models with Deep and Invertible Features Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan BDL DRL 112 99 0 07 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 104 20 0 07 Feb 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 129 810 0 07 Feb 2019
Predictive Uncertainty Quantification with Compound Density Networks Agustinus Kristiadi Sina Daubener Asja Fischer BDL UQCV 68 17 0 04 Feb 2019
HyperGAN: A Generative Model for Diverse, Performant Neural Networks Neale Ratzlaff Fuxin Li 69 64 0 30 Jan 2019
Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector Di Feng Xiao Wei Lars Rosenbaum A. Maki Klaus C. J. Dietmayer 3DPC 75 87 0 29 Jan 2019
Conditioning by adaptive sampling for robust design David H. Brookes Hahnbeom Park Jennifer Listgarten 138 199 0 29 Jan 2019
SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman Ran El-Yaniv CVBM OOD 140 311 0 26 Jan 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 130 876 0 18 Jan 2019
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference Xinyu Hu Paul A. Szerlip Theofanis Karaletsos Rohit Singh BDL AI4TS 30 5 0 17 Jan 2019
Certainty Driven Consistency Loss on Multi-Teacher Networks for Semi-Supervised Learning Lu Liu R. Tan 82 32 0 17 Jan 2019
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien UQCV 122 25 0 08 Jan 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning Peter F. Schulam Suchi Saria OOD 101 104 0 02 Jan 2019
Weakly Supervised Active Learning with Cluster Annotation Fábio Perez R. Lebret Karl Aberer 60 10 0 31 Dec 2018
Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty R. McAllister G. Kahn Jeff Clune Sergey Levine UQCV OOD 84 38 0 27 Dec 2018
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 100 10 0 18 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 184 559 0 13 Dec 2018
Efficient transfer learning and online adaptation with latent variable models for continuous control Christian F. Perez F. Such Theofanis Karaletsos OffRL 72 14 0 08 Dec 2018
MEAL: Multi-Model Ensemble via Adversarial Learning Zhiqiang Shen Zhankui He Xiangyang Xue AAML FedML 84 147 0 06 Dec 2018
Building robust classifiers through generation of confident out of distribution examples K. Sricharan Ashok Srivastava OOD 59 31 0 01 Dec 2018
Improving robustness of classifiers by training against live traffic K. Sricharan Kumar Kallurupalli Ashok Srivastava OOD TTA 36 0 0 01 Dec 2018
Evaluating Bayesian Deep Learning Methods for Semantic Segmentation Jishnu Mukhoti Y. Gal UQCV BDL 102 225 0 30 Nov 2018
Ensemble Bayesian Decision Making with Redundant Deep Perceptual Control Policies Keuntaek Lee Ziyi Wang Bogdan I. Vlahov Harleen K. Brar Evangelos A. Theodorou BDL UQCV 92 29 0 30 Nov 2018
Calibrating Uncertainties in Object Localization Task Buu Phan Rick Salay Krzysztof Czarnecki Vahdat Abdelzad Taylor Denouden Sachin Vernekar UQCV 63 22 0 27 Nov 2018
Bayesian Neural Network Ensembles Tim Pearce Mohamed H. Zaki A. Neely BDL UQCV 52 5 0 27 Nov 2018
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior Zi Wang Beomjoon Kim L. Kaelbling 74 54 0 23 Nov 2018
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization Bowen Cheng Yunchao Wei Jiahui Yu Shiyu Chang Jinjun Xiong Wen-mei W. Hwu Thomas S. Huang Humphrey Shi OOD VLM 113 6 0 23 Nov 2018
Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles Edward Grefenstette Robert Stanforth Brendan O'Donoghue J. Uesato G. Swirszcz Pushmeet Kohli AAML 80 18 0 22 Nov 2018
Sequential Neural Methods for Likelihood-free Inference Conor Durkan George Papamakarios Iain Murray BDL 184 25 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 124 420 0 19 Nov 2018
Projected BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights Melanie F. Pradier Weiwei Pan Jiayu Yao S. Ghosh Finale Doshi-velez UQCV BDL 63 10 0 16 Nov 2018
Reducing Network Agnostophobia A. Dhamija Manuel Günther Terrance E. Boult AAML UQCV 89 307 0 09 Nov 2018
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles Remus Pop Patric Fulop UQCV 66 41 0 09 Nov 2018
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles Kashyap Chitta J. Álvarez Adam Lesnikowski BDL UQCV 121 35 0 08 Nov 2018
Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels Pengxiang Cheng Jianwei Feng M. Hebert 80 17 0 08 Nov 2018
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization Matthew Maciejewski J. Álvarez Adam Lesnikowski BDL UQCV 55 3 0 06 Nov 2018
Single-Model Uncertainties for Deep Learning Natasa Tagasovska David Lopez-Paz UQCV BDL 329 25 0 02 Nov 2018
Model-Based Active Exploration Pranav Shyam Wojciech Ja'skowski Faustino J. Gomez 101 179 0 29 Oct 2018
Attended Temperature Scaling: A Practical Approach for Calibrating Deep Neural Networks A. Mozafari H. Gomes Wilson Leão Steeven Janny Christian Gagné 79 28 0 27 Oct 2018
A Gaussian Process perspective on Convolutional Neural Networks Anastasia Borovykh 81 19 0 25 Oct 2018
Do Deep Generative Models Know What They Don't Know? Eric T. Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan OOD 96 759 0 22 Oct 2018
Safe Reinforcement Learning with Model Uncertainty Estimates Björn Lütjens Michael Everett Jonathan P. How 76 169 0 19 Oct 2018