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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Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation Lars Schmarje Vasco Grossmann Claudius Zelenka S. Dippel R. Kiko ... M. Pastell J. Stracke A. Valros N. Volkmann Reinahrd Koch 37 34 0 13 Jul 2022
Sample-dependent Adaptive Temperature Scaling for Improved Calibration Thomas Joy Francesco Pinto Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 19 30 0 13 Jul 2022
On the Robustness and Anomaly Detection of Sparse Neural Networks Morgane Ayle Bertrand Charpentier John Rachwan Daniel Zügner Simon Geisler Stephan Günnemann AAML 50 3 0 09 Jul 2022
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness Francesco Pinto Harry Yang Ser-Nam Lim Philip H. S. Torr P. Dokania UQCV 27 34 0 29 Jun 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 21 0 0 27 Jun 2022
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models Liu Zhendong Wenyu Jiang Yan Zhang Chongjun Wang CML 6 0 0 22 Jun 2022
Towards OOD Detection in Graph Classification from Uncertainty Estimation Perspective Gleb Bazhenov Sergei Ivanov Maxim Panov Alexey Zaytsev Evgeny Burnaev UQCV 23 9 0 21 Jun 2022
SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation Tao Sun Mattia Segu Janis Postels Yuxuan Wang Luc Van Gool Bernt Schiele F. Tombari F. I. F. Richard Yu TTA 36 149 0 16 Jun 2022
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image Lucy Nwosu Xiangfang Li Lijun Qian Seungchan Kim Xishuang Dong 32 3 0 27 May 2022
Leveraging Causal Inference for Explainable Automatic Program Repair Jianzong Wang Shijing Si Z. Zhu Xiaoyang Qu Zhenhou Hong Jing Xiao 14 3 0 26 May 2022
Distinction Maximization Loss: Efficiently Improving Out-of-Distribution Detection and Uncertainty Estimation by Replacing the Loss and Calibrating David Macêdo Cleber Zanchettin Teresa B Ludermir UQCV 25 4 0 12 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 16 48 0 01 May 2022
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback Yuntao Bai Andy Jones Kamal Ndousse Amanda Askell Anna Chen ... Jack Clark Sam McCandlish C. Olah Benjamin Mann Jared Kaplan 69 2,308 0 12 Apr 2022
Bayesian Deep Learning with Multilevel Trace-class Neural Networks Neil K. Chada Ajay Jasra K. Law Sumeetpal S. Singh BDL UQCV 78 3 0 24 Mar 2022
Deep Ensembles Work, But Are They Necessary? Taiga Abe E. Kelly Buchanan Geoff Pleiss R. Zemel John P. Cunningham OOD UQCV 36 59 0 14 Feb 2022
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers Deebul Nair Nico Hochgeschwender Miguel A. Olivares-Mendez OOD 22 7 0 03 Feb 2022
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 21 2 0 12 Dec 2021
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection Nikolaos Dionelis Mehrdad Yaghoobi Sotirios A. Tsaftaris OODD 11 4 0 30 Nov 2021
Uncertainty Aware Proposal Segmentation for Unknown Object Detection Yimeng Li Jana Kosecka UQCV 25 19 0 25 Nov 2021
Deep Deterministic Uncertainty for Semantic Segmentation Jishnu Mukhoti Joost R. van Amersfoort Philip H. S. Torr Y. Gal BDL UQCV 47 28 0 29 Oct 2021
Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data Junjiao Tian Yen-Change Hsu Yilin Shen Hongxia Jin Z. Kira OODD 19 6 0 28 Oct 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization Sihyun Yu Sungsoo Ahn Le Song Jinwoo Shin OffRL 16 31 0 27 Oct 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification Maximilian Stadler Bertrand Charpentier Simon Geisler Daniel Zügner Stephan Günnemann UQCV BDL 28 80 0 26 Oct 2021
Uncertainty aware anomaly detection to predict errant beam pulses in the SNS accelerator S. Javed Pradeep Ramuhalli Arif Mahmood Yigit Yucesan Alexander Zhukov M. Schram Kishansingh Rajput Torri Jeske 17 15 0 22 Oct 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 26 11 0 06 Oct 2021
$Δ$ -UQ: Accurate Uncertainty Quantification via Anchor Marginalization Rushil Anirudh Jayaraman J. Thiagarajan 34 1 0 05 Oct 2021
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
Repulsive Deep Ensembles are Bayesian Francesco DÁngelo Vincent Fortuin UQCV BDL 41 93 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
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 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 16 52 0 11 May 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 H. S. Torr Y. Gal UD UQCV PER BDL 18 145 0 23 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 200 81 0 16 Feb 2021
A case for new neural network smoothness constraints Mihaela Rosca T. Weber A. Gretton S. Mohamed AAML 25 48 0 14 Dec 2020
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection Dennis Ulmer Giovanni Cina OODD 27 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 20 65 0 30 Nov 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
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 25 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 68 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 60 171 0 08 Jul 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Manifold Gaussian Processes for Regression Roberto Calandra Jan Peters C. Rasmussen M. Deisenroth 84 271 0 24 Feb 2014