Results 311 to 320 of about 3,213,103 (353)

Uncertainty quantification of antibody measurements: Physical principles and implications for standardization. [PDF]

Phys Rev E
Patrone PN, Wang L, Lin-Gibson S, Kearsley AJ.   +3 more
europepmc   +1 more source

Uncertainty quantification and error analysis

, 2010
Dave Higdon, Mark C. Anderson, Salman Habib, Richard Klein, Mark Berliner, Curt Covey, Omar Ghattas, Carlo Graziani, Mark Seager, J.A. Sefcik, Philip B. Stark, J.R. Stewart   +11 more
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Uncertainty Quantification

Oberwolfach Reports, 2020
Uncertainty quantification (UQ) is concerned with including and characterising uncertainties in mathematical models. Major steps comprise proper description of system uncertainties, analysis and efficient quantification of uncertainties in predictions and design problems, and statistical inference on uncertain parameters starting from available ...
Oliver G. Ernst, Fabio Nobile, Claudia Schillings, Tim Sullivan   +3 more
openaire   +2 more sources

FisherRF: Active View Selection and Uncertainty Quantification for Radiance Fields using Fisher Information

arXiv.org, 2023
This study addresses the challenging problem of active view selection and uncertainty quantification within the domain of Radiance Fields. Neural Radiance Fields (NeRF) have greatly advanced image rendering and reconstruction, but the cost of acquiring ...
Wen Jiang, Boshu Lei, Kostas Daniilidis
semanticscholar   +1 more source

A Survey on Uncertainty Quantification Methods for Deep Learning

ACM Computing Surveys, 2023
Deep neural networks (DNNs) have achieved tremendous success in computer vision, natural language processing, and scientific and engineering domains.
Wenchong He, Zhe Jiang
semanticscholar   +1 more source

Uncertainty Quantification

2017
This book results from a course developed by the author and reflects both his own and collaborative research regarding the development and implementation of uncertainty quantification (UQ) techniques for large-scale applications over the last two decades.The objectives of this book are to present fundamental notions for the stochastic modeling of ...
  +5 more sources

Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine

npj Digital Medicine
Digital twins in precision medicine provide tailored health recommendations by simulating patient-specific trajectories and interventions. We examine the critical role of Verification, Validation, and Uncertainty Quantification (VVUQ) for digital twins ...
Kaan Sel, Andrea Hawkins-Daarud, Anirban Chaudhuri, Deen Osman, Ahmad Bahai, David Paydarfar, Karen Willcox, Caroline Chung, Roozbeh Jafari   +8 more
semanticscholar   +1 more source

Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey

Knowledge Discovery and Data Mining
Uncertainty quantification (UQ) enhances the reliability of Large Language Models (LLMs) by estimating confidence in outputs, enabling risk mitigation and selective prediction.
Xiaoou Liu, Tiejin Chen, Longchao Da, Chacha Chen, Zhen Lin, Hua Wei   +5 more
semanticscholar   +1 more source

Distribution System Behind-the-Meter DERs: Estimation, Uncertainty Quantification, and Control

IEEE Transactions on Power Systems
This article summarizes the three-year technical activities of the IEEE Task Force (TF) on behind-the-meter (BTM) distributed energy resources (DERs): estimation, uncertainty quantification, and control.
Ankur Srivastava, Junbo Zhao, Hao Zhu, Fei Ding, Shunbo Lei, Ioannis Zografopoulos, R. Haider, Soroush Vahedi, Wenyu Wang, Gustavo Valverde, A. Gómez-Expósito, Anamika Dubey, Charalambos Konstantinou, N. Yu, Sukumar Brahma, Yuri R. Rodrigues, Mohammed Benidris, Bin Liu, Anuradha M. Annaswamy, Fankun Bu, Yishen Wang, Danny Espín-Sarzosa, Felipe Valencia, Jawana Gabrielski, Seyed Masoud Mohseni‐Bonab, Javad Jazaeri, Zhaoyu Wang, A. Srivastava   +27 more
semanticscholar   +1 more source