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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
Bayesian Neural Networks Tom Charnock Laurence Perreault Levasseur F. Lanusse UQCV BDL 29 3 0 02 Jun 2020
Fully probabilistic quasar continua predictions near Lyman-α with conditional neural spline flows D. Reiman John Tamanas J. Prochaska Dominika Ďurovčíková 57 6 0 31 May 2020
MOPO: Model-based Offline Policy Optimization Tianhe Yu G. Thomas Lantao Yu Stefano Ermon James Zou Sergey Levine Chelsea Finn Tengyu Ma OffRL 103 775 0 27 May 2020
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification Sina Daubener Lea Schonherr Asja Fischer D. Kolossa AAML 71 18 0 24 May 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties J. Lindinger David Reeb C. Lippert Barbara Rakitsch BDL UQCV 74 8 0 22 May 2020
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation Hong Joo Lee S. T. Kim Hakmin Lee Nassir Navab Yong Man Ro UQCV 83 7 0 21 May 2020
Unsupervised Quality Estimation for Neural Machine Translation M. Fomicheva Shuo Sun Lisa Yankovskaya Frédéric Blain Francisco Guzmán Mark Fishel Nikolaos Aletras Vishrav Chaudhary Lucia Specia UQLM 91 209 0 21 May 2020
Inferring astrophysical X-ray polarization with deep learning N. Moriakov Ashwin Samudre M. Negro Fabian Gieseke Sydney Otten L. Hendriks 21 3 0 16 May 2020
Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones? Nadezhda Chirkova E. Lobacheva Dmitry Vetrov OOD MoE 51 9 0 14 May 2020
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms J. Caldeira Brian D. Nord BDL UQCV UD 91 81 0 22 Apr 2020
Deep State Space Models for Nonlinear System Identification Daniel Gedon Niklas Wahlström Thomas B. Schon L. Ljung 69 88 0 31 Mar 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 86 6 0 22 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 61 7 0 17 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Yue Liu P. Varshney Basel Alomair AAML 163 47 0 16 Mar 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks Amir M. Rahimi Amirreza Shaban Ching-An Cheng Leonid Sigal Byron Boots UQCV 243 70 0 15 Mar 2020
Diversity inducing Information Bottleneck in Model Ensembles Samarth Sinha Homanga Bharadhwaj Anirudh Goyal Hugo Larochelle Animesh Garg Florian Shkurti BDL UQCV 63 40 0 10 Mar 2020
Dropout Strikes Back: Improved Uncertainty Estimation via Diversity Sampling Kirill Fedyanin Evgenii Tsymbalov Maxim Panov UQCV 41 7 0 06 Mar 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 110 55 0 04 Mar 2020
Automatic Differentiation Variational Inference with Mixtures Warren Morningstar Sharad M. Vikram Cusuh Ham Andrew Gallagher Joshua V. Dillon DRL BDL 59 20 0 03 Mar 2020
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation Sangdon Park Osbert Bastani James Weimer Insup Lee 69 53 0 29 Feb 2020
A general framework for ensemble distribution distillation Jakob Lindqvist Amanda Olmin Fredrik Lindsten Lennart Svensson FedML UQCV BDL 75 19 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 90 290 0 24 Feb 2020
On the Role of Dataset Quality and Heterogeneity in Model Confidence Yuan Zhao Jiasi Chen Samet Oymak 53 14 0 23 Feb 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 96 468 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 109 85 0 21 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 172 657 0 20 Feb 2020
Uncertainty Estimation in Autoregressive Structured Prediction A. Malinin Mark Gales UQLM 72 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 179 38 0 18 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 218 494 0 17 Feb 2020
Active Bayesian Assessment for Black-Box Classifiers Disi Ji Robert L Logan IV Padhraic Smyth M. Steyvers UQCV 41 17 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 108 320 0 15 Feb 2020
Learning to Predict Error for MRI Reconstruction Shi Hu Nicola Pezzotti Max Welling UQCV 59 14 0 13 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 137 30 0 13 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 104 24 0 10 Feb 2020
Semi-Supervised Class Discovery Jeremy Nixon J. Liu David Berthelot 65 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 72 47 0 07 Feb 2020
The Case for Bayesian Deep Learning A. Wilson UQCV BDL OOD 132 114 0 29 Jan 2020
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification Lynton Ardizzone Radek Mackowiak Ullrich Kothe Carsten Rother UQCV 66 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 98 59 0 14 Jan 2020
On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration Kanil Patel William H. Beluch Dan Zhang Michael Pfeiffer Bin Yang UQCV 125 30 0 16 Dec 2019
Bayesian Variational Autoencoders for Unsupervised Out-of-Distribution Detection Erik A. Daxberger José Miguel Hernández-Lobato UQCV 103 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 36 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 183 1,313 0 05 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 157 631 0 05 Dec 2019
Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning Samuel Kessler Vu Nguyen S. Zohren Stephen J. Roberts BDL 94 25 0 04 Dec 2019
A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift A. Mozafari H. Gomes Christian Gagné 28 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 71 23 0 19 Nov 2019
Implicit Generative Modeling for Efficient Exploration Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu 70 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 110 52 0 18 Nov 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 126 329 0 25 Oct 2019