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ArticleA unified framework for multilevel uncertainty quantification in Bayesian inverse problems

Joseph B. Nagel2015

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Articlegreen2015

A unified framework for multilevel uncertainty quantification in Bayesian inverse problems

Joseph B. Nagel · Bruno Sudret

103 citations·0/0 files stored·Probabilistic Engineering Mechanics

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Probabilistic and Robust Engineering Design Statistical Methods and Bayesian Inference Gaussian Processes and Bayesian Inference

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References

2008Aleatory or epistemic? Does it matter?2006Stochastic spectral methods for efficient Bayesian solution of inverse problems 2012Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability 2004Alternative representations of epistemic uncertainty 1993Combining Information: Statistical Issues and Opportunities for Research 2008Bayesian inference in probabilistic risk assessment—The current state of the art 2005Maximum likelihood estimation of stochastic chaos representations from experimental data

Cited by

2019Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation 2024Dimensional decomposition-aided metamodels for uncertainty quantification and optimization in engineering: A review 2020Basic Framework and Main Methods of Uncertainty Quantification 2021Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric 2023Recent advances in uncertainty quantification in structural response characterization and system identification

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Year2015

Typearticle

Published2015-09-14

VenueProbabilistic Engineering Mechanics

ISSN-L0266-8920

Languageen

Citations103

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1016/j.probengmech.2015.09.007

openalex_workW2236462275

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2018

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