How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?

7 February 2023

Papers citing "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?"

7 / 7 papers shown

Title
Cooperative Bayesian and variance networks disentangle aleatoric and epistemic uncertainties Jiaxiang Yi Miguel A. Bessa UD PER UQCV 37 0 0 05 May 2025
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning Nils Lehmann Jakob Gawlikowski Adam J. Stewart Vytautas Jancauskas Stefan Depeweg Eric T. Nalisnick N. Gottschling 35 0 0 04 Oct 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift Benjamin Eyre Elliot Creager David Madras Antonio Torralba Katherine Heller OOD OODD 23 1 0 29 Dec 2023
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification Leo Schwinn Leon Bungert A. Nguyen René Raab Falk Pulsmeyer Doina Precup Björn Eskofier Dario Zanca OOD 42 12 0 19 May 2022
A Fine-Grained Analysis on Distribution Shift Olivia Wiles Sven Gowal Florian Stimberg Sylvestre-Alvise Rebuffi Ira Ktena Krishnamurthy Dvijotham A. Cemgil OOD 215 201 0 21 Oct 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015