Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity

12 September 2023

Papers citing "Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity"

8 / 8 papers shown

Title
Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios Ciaran Bench Emir Ahmed Spencer A. Thomas MedIm 36 0 0 29 Jan 2025
Materials-Discovery Workflows Guided by Symbolic Regression: Identifying Acid-Stable Oxides for Electrocatalysis Akhil S. Nair L. Foppa Matthias Scheffler 59 1 0 08 Dec 2024
On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks Pascal Pernot 19 0 0 23 Aug 2024
Uncertainty Quantification in Large Language Models Through Convex Hull Analysis Ferhat Ozgur Catak Murat Kuzlu UQCV 47 4 0 28 Jun 2024
Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysis Pascal Pernot 19 0 0 01 Mar 2024
Negative impact of heavy-tailed uncertainty and error distributions on the reliability of calibration statistics for machine learning regression tasks Pascal Pernot 33 1 0 15 Feb 2024
Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ? Pascal Pernot 15 2 0 18 Oct 2023
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification Youngseog Chung I. Char Han Guo J. Schneider W. Neiswanger 30 70 0 21 Sep 2021