Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules

16 February 2024

Papers citing "Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules"

7 / 7 papers shown

Title
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph Roman Vashurin Ekaterina Fadeeva Artem Vazhentsev Akim Tsvigun Daniil Vasilev ... Timothy Baldwin Timothy Baldwin Maxim Panov Artem Shelmanov Artem Shelmanov HILM 59 7 0 21 Jun 2024
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification Viktor Bengs Eyke Hüllermeier Willem Waegeman UQCV 195 25 0 30 Jan 2023
Nonparametric Uncertainty Quantification for Single Deterministic Neural Network Nikita Kotelevskii A. Artemenkov Kirill Fedyanin Fedor Noskov Alexander Fishkov Artem Shelmanov Artem Vazhentsev Aleksandr Petiushko Maxim Panov UQCV BDL 37 25 0 07 Feb 2022
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 195 80 0 16 Feb 2021
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 278 10,544 0 19 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015