Easy uncertainty quantification (EasyUQ): Generating predictive distributions from single-valued model output

Abstract:
No abstract specified

SEEK ID: https://publications.h-its.org/publications/1782

Filename: 22m1541915.pdf 

Format: PDF document

Size: 1.47 MB

SEEK ID: https://publications.h-its.org/publications/1782

DOI: 10.1137/22M1541915

Research Groups: Computational Statistics

Publication type: Journal

Journal: SIAM Review

Citation: SIAM Review, 66(1):91–122

Date Published: 8th Feb 2024

URL:

Registered Mode: manually

Authors: Eva-Maria Walz, Alexander Henzi, Johanna Ziegel, Tilmann Gneiting

Citation
Walz, E.-M., Henzi, A., Ziegel, J., & Gneiting, T. (2024). Easy Uncertainty Quantification (EasyUQ): Generating Predictive Distributions from Single-Valued Model Output. In SIAM Review (Vol. 66, Issue 1, pp. 91–122). Society for Industrial & Applied Mathematics (SIAM). https://doi.org/10.1137/22m1541915
Activity

Views: 584   Downloads: 7

Created: 8th Feb 2024 at 11:31

Last updated: 8th Mar 2024 at 13:07

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.14.2)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH