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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Title
On the Role of Dataset Quality and Heterogeneity in Model Confidence Yuan Zhao Jiasi Chen Samet Oymak 27 12 0 23 Feb 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 56 445 0 21 Feb 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation Dmitry Molchanov Alexander Lyzhov Yuliya Molchanova Arsenii Ashukha Dmitry Vetrov TPM 27 84 0 21 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 641 0 20 Feb 2020
Uncertainty Estimation in Autoregressive Structured Prediction A. Malinin Mark Gales UQLM 22 9 0 18 Feb 2020
Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability Yikai Yan Chaoyue Niu Yucheng Ding Zhenzhe Zheng Fan Wu Guihai Chen Shaojie Tang Zhihua Wu FedML 49 37 0 18 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 32 483 0 17 Feb 2020
Active Bayesian Assessment for Black-Box Classifiers Disi Ji Robert L Logan IV Padhraic Smyth M. Steyvers UQCV 8 15 0 16 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 35 314 0 15 Feb 2020
Learning to Predict Error for MRI Reconstruction Shi Hu Nicola Pezzotti Max Welling UQCV 6 14 0 13 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 19 28 0 13 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 20 23 0 10 Feb 2020
Semi-Supervised Class Discovery Jeremy Nixon J. Liu David Berthelot 20 2 0 10 Feb 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks J. Swiatkowski Kevin Roth Bastiaan S. Veeling Linh-Tam Tran Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Rodolphe Jenatton Sebastian Nowozin BDL 31 45 0 07 Feb 2020
The Case for Bayesian Deep Learning A. Wilson UQCV BDL OOD 17 110 0 29 Jan 2020
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification Lynton Ardizzone Radek Mackowiak Ullrich Kothe Carsten Rother UQCV 10 4 0 17 Jan 2020
Hydra: Preserving Ensemble Diversity for Model Distillation Linh-Tam Tran Bastiaan S. Veeling Kevin Roth J. Swiatkowski Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Sebastian Nowozin Rodolphe Jenatton 21 58 0 14 Jan 2020
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 27 30 0 16 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection Erik A. Daxberger José Miguel Hernández-Lobato UQCV 18 63 0 11 Dec 2019
Individual predictions matter: Assessing the effect of data ordering in training fine-tuned CNNs for medical imaging J. Zech Jessica Zosa Forde Michael L. Littman 21 5 0 08 Dec 2019
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty Dan Hendrycks Norman Mu E. D. Cubuk Barret Zoph Justin Gilmer Balaji Lakshminarayanan OOD UQCV 48 1,280 0 05 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 38 619 0 05 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 16 23 0 04 Dec 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift A. Mozafari H. Gomes Christian Gagné 14 0 0 25 Nov 2019
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks Héctor J. Hortúa Riccardo Volpi D. Marinelli Luigi Malagò BDL 13 22 0 19 Nov 2019
Implicit Generative Modeling for Efficient Exploration Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu 22 12 0 19 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 45 314 0 25 Oct 2019
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty T. LaBonte Carianne Martinez S. Roberts UQCV 3DV 20 31 0 23 Oct 2019
Detecting Underspecification with Local Ensembles David Madras James Atwood Alexander DÁmour 35 4 0 21 Oct 2019
NGBoost: Natural Gradient Boosting for Probabilistic Prediction Tony Duan Anand Avati D. Ding Khanh K. Thai S. Basu A. Ng Alejandro Schuler BDL 6 295 0 08 Oct 2019
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 18 105 0 21 Sep 2019
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers? Martin Mundt Iuliia Pliushch Sagnik Majumder Visvanathan Ramesh UQCV EDL 13 40 0 26 Aug 2019
Vector Quantized Bayesian Neural Network Inference for Data Streams Namuk Park Taekyu Lee Songkuk Kim MQ 22 9 0 12 Jul 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 50 716 0 07 Jun 2019
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision Fredrik K. Gustafsson Martin Danelljan Thomas B. Schon OOD UQCV BDL 30 295 0 04 Jun 2019
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition Martin Mundt Iuliia Pliushch Sagnik Majumder Yongwon Hong Visvanathan Ramesh UQCV BDL 27 40 0 28 May 2019
Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions Feiyang Pan Xiang Ao Pingzhong Tang Min Lu Dapeng Liu Lei Xiao Qing He 30 22 0 26 May 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 27 231 0 30 Apr 2019
A Roadmap for Robust End-to-End Alignment L. Hoang 28 1 0 04 Sep 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015