Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

17 June 2020

Balaji Lakshminarayanan

UQCV

BDL

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Papers citing "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness"

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Title
No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets Fahim Tajwar Ananya Kumar Sang Michael Xie Percy Liang OODD 22 21 0 12 Sep 2021
Uncertainty-Aware Credit Card Fraud Detection Using Deep Learning Maryam Habibpour Hassan Gharoun M. Mehdipour AmirReza Tajally Hamzeh Asgharnezhad Afshar Shamsi Jokandan Abbas Khosravi M. Shafie‐khah S. Nahavandi J. Catalão 25 45 0 28 Jul 2021
Epistemic Neural Networks Ian Osband Zheng Wen M. Asghari Vikranth Dwaracherla M. Ibrahimi Xiyuan Lu Benjamin Van Roy UQCV BDL 30 97 0 19 Jul 2021
BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark Anand Avati Martin G. Seneviratne Emily Xue Zhen Xu Balaji Lakshminarayanan Andrew M. Dai OOD CML 20 8 0 17 Jul 2021
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks A. Malinin Neil Band Ganshin Alexander German Chesnokov ... Roginskiy Denis Mariya Shmatova Panos Tigas Boris Yangel UQCV OOD 29 127 0 15 Jul 2021
What classifiers know what they don't? Mohamed Ishmael Belghazi David Lopez-Paz 22 6 0 13 Jul 2021
Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation Ian D Kivlichan Zi Lin J. Liu Lucy Vasserman 14 19 0 09 Jul 2021
Towards Robust Active Feature Acquisition Yang Li Siyuan Shan Qin Liu Junier B. Oliva TPM 15 4 0 09 Jul 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool F. I. F. Richard Yu Federico Tombari UQCV 25 59 0 01 Jul 2021
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 53 94 0 22 Jun 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection Jie Jessie Ren Stanislav Fort J. Liu Abhijit Guha Roy Shreyas Padhy Balaji Lakshminarayanan UQCV 33 216 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
Understanding Softmax Confidence and Uncertainty Tim Pearce Alexandra Brintrup Jun Zhu UQCV 14 87 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 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 29 96 0 07 Jun 2021
Can a single neuron learn predictive uncertainty? Edgardo Solano-Carrillo UQCV 29 1 0 07 Jun 2021
Exploring the Limits of Out-of-Distribution Detection Stanislav Fort Jie Jessie Ren Balaji Lakshminarayanan 27 325 0 06 Jun 2021
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective Lewis Smith Joost R. van Amersfoort Haiwen Huang Stephen J. Roberts Y. Gal 25 7 0 04 Jun 2021
Enhanced Isotropy Maximization Loss: Seamless and High-Performance Out-of-Distribution Detection Simply Replacing the SoftMax Loss David Macêdo Teresa B Ludermir OODD 23 12 0 30 May 2021
Understanding Uncertainty in Bayesian Deep Learning Cooper Lorsung BDL UQCV 4 0 0 21 May 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 31 124 0 14 May 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 21 52 0 11 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions Bertrand Charpentier Oliver Borchert Daniel Zügner Simon Geisler Stephan Günnemann UQCV BDL 27 17 0 10 May 2021
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties Lisa Schut Oscar Key R. McGrath Luca Costabello Bogdan Sacaleanu Medb Corcoran Y. Gal CML 17 47 0 16 Mar 2021
Posterior Meta-Replay for Continual Learning Christian Henning Maria R. Cervera Francesco DÁngelo J. Oswald Regina Traber Benjamin Ehret Seijin Kobayashi Benjamin Grewe João Sacramento CLL BDL 51 54 0 01 Mar 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 21 107 0 24 Feb 2021
Deep Deterministic Uncertainty: A Simple Baseline Jishnu Mukhoti Andreas Kirsch Joost R. van Amersfoort Philip Torr Y. Gal UD UQCV PER BDL 24 145 0 23 Feb 2021
On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty Joost R. van Amersfoort Lewis Smith Andrew Jesson Oscar Key Y. Gal UQCV 24 102 0 22 Feb 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 204 81 0 16 Feb 2021
Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification Yu Bai Song Mei Haiquan Wang Caiming Xiong 17 42 0 15 Feb 2021
Estimation and Applications of Quantiles in Deep Binary Classification Anuj Tambwekar Anirudh Maiya S. Dhavala Snehanshu Saha UQCV 8 7 0 09 Feb 2021
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection Alexander Podolskiy Dmitry Lipin A. Bout Ekaterina Artemova Irina Piontkovskaya OODD 95 82 0 11 Jan 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber A. Gretton S. Mohamed AAML 33 48 0 14 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer Giovanni Cina OODD 35 31 0 09 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 22 65 0 30 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 22 247 0 15 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 51 1,879 0 12 Nov 2020
Hierarchical Gaussian Processes with Wasserstein-2 Kernels S. Popescu D. Sharp James H. Cole Ben Glocker 22 5 0 28 Oct 2020
Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures Benjamin Kompa Jasper Snoek Andrew L. Beam UQCV BDL 26 29 0 06 Oct 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
An Uncertainty-aware Transfer Learning-based Framework for Covid-19 Diagnosis Afshar Shamsi Hamzeh Asgharnezhad Shirin Shamsi Jokandan Abbas Khosravi P. Kebria D. Nahavandi S. Nahavandi D. Srinivasan OOD 8 133 0 26 Jul 2020
Uncertainty-Aware (UNA) Bases for Deep Bayesian Regression Using Multi-Headed Auxiliary Networks Sujay Thakur Cooper Lorsung Yaniv Yacoby Finale Doshi-Velez Weiwei Pan BDL UQCV 27 4 0 21 Jun 2020
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 73 31 0 13 Apr 2018
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks John Bradshaw A. G. Matthews Zoubin Ghahramani BDL AAML 68 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 89 271 0 24 Feb 2014