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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
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs Cheng Wang Carolin (Haas) Lawrence Mathias Niepert UQCV 58 10 0 24 Nov 2020
Provably-Robust Runtime Monitoring of Neuron Activation Patterns Chih-Hong Cheng AAML 78 12 0 24 Nov 2020
Dense open-set recognition with synthetic outliers generated by Real NVP Matej Grcić Petra Bevandić Sinisa Segvic 67 41 0 22 Nov 2020
A Review and Comparative Study on Probabilistic Object Detection in Autonomous Driving Di Feng Ali Harakeh Steven Waslander Klaus C. J. Dietmayer AAML UQCV EDL 126 227 0 20 Nov 2020
Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry Yizhou Qian M. Forghani Jonghyun Lee Matthew W. Farthing T. Hesser P. Kitanidis Eric F. Darve AI4CE 43 5 0 19 Nov 2020
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung Willie Neiswanger I. Char J. Schneider UQCV 209 89 0 18 Nov 2020
Positive-Congruent Training: Towards Regression-Free Model Updates Sijie Yan Yuanjun Xiong Kaustav Kundu Shuo Yang Siqi Deng Meng Wang Wei Xia Stefano Soatto BDL 93 53 0 18 Nov 2020
Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data Aastha Acharya Rebecca L. Russell Nisar R. Ahmed OffRL 48 4 0 17 Nov 2020
A Simple Framework to Quantify Different Types of Uncertainty in Deep Neural Networks for Image Classification A. Khoshsirat UQCV 16 0 0 17 Nov 2020
DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference Jiyang Xie Zhanyu Ma Jing-Hao Xue Guoqiang Zhang Jun Guo BDL 46 11 0 17 Nov 2020
Fast Uncertainty Quantification for Deep Object Pose Estimation Guanya Shi Yifeng Zhu Jonathan Tremblay Stan Birchfield F. Ramos Anima Anandkumar Yuke Zhu 76 26 0 16 Nov 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 129 252 0 15 Nov 2020
Automatic segmentation with detection of local segmentation failures in cardiac MRI Jörg Sander B. D. de Vos Ivana Išgum 99 50 0 13 Nov 2020
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models Lijing Wang Dipanjan Ghosh Maria Teresa Gonzalez Diaz Ahmed K. Farahat M. Alam Chetan Gupta Jiangzhuo Chen Madhav Marathe 43 10 0 13 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 369 1,947 0 12 Nov 2020
A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning Hany Abdulsamad Peter Nickl Pascal Klink Jan Peters 23 3 0 10 Nov 2020
Efficient and Transferable Adversarial Examples from Bayesian Neural Networks Martin Gubri Maxime Cordy Mike Papadakis Yves Le Traon Koushik Sen AAML 151 11 0 10 Nov 2020
Improving Classifier Confidence using Lossy Label-Invariant Transformations Sooyong Jang Insup Lee James Weimer UQCV 44 7 0 09 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 174 688 0 06 Nov 2020
Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data Dennis Ulmer L. Meijerink Giovanni Cina OOD 48 73 0 06 Nov 2020
Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations? Chaoqi Wang Shengyang Sun Roger C. Grosse UQCV 71 25 0 06 Nov 2020
Generalized Negative Correlation Learning for Deep Ensembling Sebastian Buschjäger Lukas Pfahler K. Morik FedML BDL UQCV 69 17 0 05 Nov 2020
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation Aurick Zhou Sergey Levine BDL OOD UQCV 56 13 0 05 Nov 2020
The Aleatoric Uncertainty Estimation Using a Separate Formulation with Virtual Residuals Takumi Kawashima Qing Yu Akari Asai Daiki Ikami Kiyoharu Aizawa 37 6 0 03 Nov 2020
Scheduling Real-time Deep Learning Services as Imprecise Computations Shuochao Yao Yifan Hao Yiran Zhao Huajie Shao Dongxin Liu Shengzhong Liu Tianshi Wang Jinyang Li Tarek Abdelzaher 108 36 0 02 Nov 2020
PAC Confidence Predictions for Deep Neural Network Classifiers Sangdon Park Shuo Li Insup Lee Osbert Bastani UQCV 115 27 0 02 Nov 2020
Bayesian Optimization Meets Laplace Approximation for Robotic Introspection Matthias Humt Jongseo Lee Rudolph Triebel BDL UQCV 78 11 0 30 Oct 2020
deep21: a Deep Learning Method for 21cm Foreground Removal T. Lucas Makinen Lachlan Lancaster F. Villaescusa-Navarro Peter Melchior S. Ho Laurence Perreault Levasseur D. Spergel 3DPC 56 30 0 29 Oct 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? Anna-Kathrin Kopetzki Bertrand Charpentier Daniel Zügner Sandhya Giri Stephan Günnemann 82 48 0 28 Oct 2020
Hierarchical Gaussian Processes with Wasserstein-2 Kernels S. Popescu D. Sharp James H. Cole Ben Glocker 74 5 0 28 Oct 2020
Bayesian Methods for Semi-supervised Text Annotation Kristian Miok Gregor Pirš Marko Robnik-Šikonja BDL 51 5 0 28 Oct 2020
Bayesian Deep Learning via Subnetwork Inference Erik A. Daxberger Eric T. Nalisnick J. Allingham Javier Antorán José Miguel Hernández-Lobato UQCV BDL 130 86 0 28 Oct 2020
Learning to Plan Optimistically: Uncertainty-Guided Deep Exploration via Latent Model Ensembles Tim Seyde Wilko Schwarting S. Karaman Daniela Rus 100 14 0 27 Oct 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 102 24 0 27 Oct 2020
Selective Classification Can Magnify Disparities Across Groups Erik Jones Shiori Sagawa Pang Wei Koh Ananya Kumar Percy Liang 115 47 0 27 Oct 2020
Know Where To Drop Your Weights: Towards Faster Uncertainty Estimation A. Kamath Dwaraknath Gnaneshwar Matias Valdenegro-Toro BDL UQCV 16 1 0 27 Oct 2020
Scalable Bayesian neural networks by layer-wise input augmentation Trung Trinh Samuel Kaski Markus Heinonen UQCV BDL 36 3 0 26 Oct 2020
AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild Zhe Zhang Chunyu Wang Weichao Qiu Wenhu Qin Wenjun Zeng 3DH 104 89 0 26 Oct 2020
Out-of-distribution detection for regression tasks: parameter versus predictor entropy Y. Pequignot Mathieu Alain Patrick Dallaire Alireza Yeganehparast Pascal Germain Josée Desharnais Franccois Laviolette OODD 36 2 0 24 Oct 2020
PEP: Parameter Ensembling by Perturbation Alireza Mehrtash Purang Abolmaesumi Polina Golland Tina Kapur Demian Wassermann W. Wells 70 10 0 24 Oct 2020
On the Embeddings of Variables in Recurrent Neural Networks for Source Code Nadezhda Chirkova 33 0 0 23 Oct 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data Lingkai Kong Haoming Jiang Yuchen Zhuang Jie Lyu T. Zhao Chao Zhang OODD 91 26 0 22 Oct 2020
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data Chacha Chen Junjie Liang Fenglong Ma Lucas Glass Jimeng Sun Cao Xiao 71 26 0 22 Oct 2020
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples Jay Nandy Wynne Hsu Mong Li Lee UQCV 92 61 0 20 Oct 2020
Smooth activations and reproducibility in deep networks G. Shamir Dong Lin Lorenzo Coviello 66 23 0 20 Oct 2020
Anti-Distillation: Improving reproducibility of deep networks G. Shamir Lorenzo Coviello 106 19 0 19 Oct 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 139 64 0 19 Oct 2020
Stationary Activations for Uncertainty Calibration in Deep Learning Lassi Meronen Christabella Irwanto Arno Solin UQCV BDL 54 19 0 19 Oct 2020
Double-Uncertainty Weighted Method for Semi-supervised Learning Yixin Wang Yao Zhang Jiang Tian Cheng Zhong Zhongchao Shi Yang Zhang Zhiqiang He UQCV 68 116 0 19 Oct 2020
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination Cole Hawkins Xing-er Liu Zheng Zhang BDL MQ 114 29 0 17 Oct 2020