Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

6 June 2019

Balaji Lakshminarayanan

Jasper Snoek

UQCV

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Papers citing "Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift"

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Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation Ian D Kivlichan Zi Lin J. Liu Lucy Vasserman 22 19 0 09 Jul 2021
Towards Robust Active Feature Acquisition Yang Li Siyuan Shan Qin Liu Junier B. Oliva TPM 18 4 0 09 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 66 1,112 0 07 Jul 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 30 117 0 07 Jul 2021
Test for non-negligible adverse shifts Vathy M. Kamulete 20 3 0 07 Jul 2021
Detecting Concept Drift With Neural Network Model Uncertainty Lucas Baier Tim Schlör Jakob Schöffer Niklas Kühl 27 27 0 05 Jul 2021
Mitigating Uncertainty of Classifier for Unsupervised Domain Adaptation Shanu Kumar V. Kurmi Praphul Singh Vinay P. Namboodiri 23 4 0 01 Jul 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 38 60 0 01 Jul 2021
Unsupervised Model Drift Estimation with Batch Normalization Statistics for Dataset Shift Detection and Model Selection Won-Jo Lee Seokhyun Byun Jooeun Kim Minje Park Kirill Chechil AI4TS 26 2 0 01 Jul 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles Jiefeng Chen Frederick Liu Besim Avci Xi Wu Yingyu Liang S. Jha 32 61 0 29 Jun 2021
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis Linyi Yang Jiazheng Li Padraig Cunningham Yue Zhang Barry Smyth Ruihai Dong 27 47 0 29 Jun 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 63 290 0 28 Jun 2021
Ensembling Shift Detectors: an Extensive Empirical Evaluation Simona Maggio L. Dreyfus-Schmidt AI4TS 34 3 0 28 Jun 2021
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity Shiwei Liu Tianlong Chen Zahra Atashgahi Xiaohan Chen Ghada Sokar Elena Mocanu Mykola Pechenizkiy Zhangyang Wang Decebal Constantin Mocanu OOD 31 49 0 28 Jun 2021
Scene Uncertainty and the Wellington Posterior of Deterministic Image Classifiers Stephanie Tsuei Aditya Golatkar Stefano Soatto UQCV 29 0 0 25 Jun 2021
FF-NSL: Feed-Forward Neural-Symbolic Learner Daniel Cunnington Mark Law A. Russo Jorge Lobo NAI 42 15 0 24 Jun 2021
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space Kalun Ho Franz-Josef Pfreundt J. Keuper Margret Keuper OOD UQCV 22 3 0 23 Jun 2021
Towards Consistent Predictive Confidence through Fitted Ensembles Navid Kardan Ankit Sharma Kenneth O. Stanley FedML OODD 21 8 0 22 Jun 2021
Dangers of Bayesian Model Averaging under Covariate Shift Pavel Izmailov Patrick K. Nicholson Sanae Lotfi A. Wilson OOD UQCV BDL 32 45 0 22 Jun 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 64 95 0 22 Jun 2021
On Stein Variational Neural Network Ensembles Francesco DÁngelo Vincent Fortuin F. Wenzel UQCV BDL 41 25 0 20 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 23 15 0 18 Jun 2021
Gradual Domain Adaptation via Self-Training of Auxiliary Models Yabin Zhang Bin Deng Kui Jia Lei Zhang CLL 28 10 0 18 Jun 2021
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error Ondrej Bohdal Yongxin Yang Timothy M. Hospedales UQCV OOD 47 21 0 17 Jun 2021
On Deep Neural Network Calibration by Regularization and its Impact on Refinement Aditya Singh Alessandro Bay B. Sengupta Andrea Mirabile AAML 27 2 0 17 Jun 2021
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL Catherine Cang Aravind Rajeswaran Pieter Abbeel Michael Laskin OffRL 32 29 0 16 Jun 2021
Test Sample Accuracy Scales with Training Sample Density in Neural Networks Xu Ji Razvan Pascanu Devon Hjelm Balaji Lakshminarayanan Andrea Vedaldi 36 7 0 15 Jun 2021
Revisiting the Calibration of Modern Neural Networks Matthias Minderer Josip Djolonga Rob Romijnders F. Hubis Xiaohua Zhai N. Houlsby Dustin Tran Mario Lucic UQCV 51 358 0 15 Jun 2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci Kevin Roth Gregor Bachmann Sebastian Nowozin Thomas Hofmann CML 30 23 0 11 Jun 2021
Locally Sparse Neural Networks for Tabular Biomedical Data Junchen Yang Ofir Lindenbaum Y. Kluger 35 33 0 11 Jun 2021
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? Weijian Deng Stephen Gould Liang Zheng 39 63 0 10 Jun 2021
Understanding the Under-Coverage Bias in Uncertainty Estimation Yu Bai Song Mei Huan Wang Caiming Xiong UQCV 23 13 0 10 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation David Berthelot Rebecca Roelofs Kihyuk Sohn Nicholas Carlini Alexey Kurakin 29 136 0 08 Jun 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Zachary Nado Neil Band Mark Collier Josip Djolonga Michael W. Dusenberry ... D. Sculley Balaji Lakshminarayanan Jasper Snoek Y. Gal Dustin Tran UQCV ELM 38 96 0 07 Jun 2021
Shifting Transformation Learning for Out-of-Distribution Detection Sina Mohseni Arash Vahdat J. Yadawa OODD 33 7 0 07 Jun 2021
Counterfactual Maximum Likelihood Estimation for Training Deep Networks Xinyi Wang Wenhu Chen Michael Stephen Saxon Wenjie Wang OOD CML BDL 23 8 0 07 Jun 2021
Frustratingly Easy Uncertainty Estimation for Distribution Shift Tiago Salvador Vikram S. Voleti Alexander Iannantuono Adam M. Oberman OOD UQCV 28 1 0 07 Jun 2021
Can a single neuron learn predictive uncertainty? Edgardo Solano-Carrillo UQCV 34 1 0 07 Jun 2021
Evidential Turing Processes M. Kandemir Abdullah Akgul Manuel Haussmann Gözde B. Ünal EDL UQCV BDL 33 9 0 02 Jun 2021
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals Jirí Navrátil Benjamin Elder Matthew Arnold S. Ghosh P. Sattigeri 25 5 0 01 Jun 2021
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning Maxime Vono Vincent Plassier Alain Durmus Aymeric Dieuleveut Eric Moulines FedML 43 35 0 01 Jun 2021
Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift Sebastian Cygert Bartlomiej Wróblewski Karol Wozniak Radoslaw Slowiñski A. Czyżewski UQCV OOD 39 7 0 31 May 2021
Sparse Uncertainty Representation in Deep Learning with Inducing Weights H. Ritter Martin Kukla Chen Zhang Yingzhen Li UQCV BDL 63 17 0 30 May 2021
Greedy Bayesian Posterior Approximation with Deep Ensembles A. Tiulpin Matthew B. Blaschko UQCV FedML 36 4 0 29 May 2021
Learning Uncertainty For Safety-Oriented Semantic Segmentation In Autonomous Driving Victor Besnier David Picard Alexandre Briot UQCV 22 11 0 28 May 2021
Deep Ensembles from a Bayesian Perspective L. Hoffmann Clemens Elster UD BDL UQCV 22 36 0 27 May 2021
Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness Namuk Park S. Kim UQCV AAML 25 19 0 26 May 2021
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling Akis Linardos Matthias Kümmerer Ori Press Matthias Bethge MDE 24 65 0 26 May 2021
Mapping oil palm density at country scale: An active learning approach Andrés C. Rodríguez Stefano Dáronco Konrad Schindler Jan Dirk Wegner 37 40 0 24 May 2021