A framework for benchmarking uncertainty in deep regression

10 September 2021

Papers citing "A framework for benchmarking uncertainty in deep regression"

7 / 7 papers shown

Title
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 42 0 0 04 Oct 2024
Measurement Uncertainty: Relating the uncertainties of physical and virtual measurements Simon Cramer Tobias Müller Robert H. Schmitt 27 2 0 21 Feb 2024
MUBen: Benchmarking the Uncertainty of Molecular Representation Models Yinghao Li Lingkai Kong Yuanqi Du Yue Yu Yuchen Zhuang Wenhao Mu Chao Zhang 27 9 0 14 Jun 2023
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification Youngseog Chung I. Char Han Guo J. Schneider W. Neiswanger 38 70 0 21 Sep 2021
Aleatoric uncertainty for Errors-in-Variables models in deep regression J. Martin Clemens Elster UQCV UD BDL 17 8 0 19 May 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,636 0 03 Jul 2012