A Gaussian Process Emulator Based Approach for Bayesian Calibration of a Functional Input-Reference-Cited by-同舟云学术

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A Gaussian Process Emulator Based Approach for Bayesian Calibration of a Functional Input

Published:2021-10-19 Issue: Volume: Page:1-13
ISSN:0040-1706
Container-title:Technometrics
language:en
Short-container-title:Technometrics

Author:

Li Zhaohui¹²³^ORCID,Tan Matthias Hwai Yong¹⁴

Affiliation:

1. School of Data Science, City University of Hong Kong, Kowloon, Hong Kong;;

2. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;;

3. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China

4. Hong Kong Institute for Data Science (HKIDS), City University of Hong Kong, Kowloon, Hong Kong;;

Funder

Research Grants Council of the Hong Kong Special Administrative Region, China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00401706.2021.1971567

Reference53 articles.

1. Analysis of the Gibbs Sampler for Hierarchical Inverse Problems

2. Estimation of heterogeneous aquifer parameters using centralized and decentralized fusion of hydraulic tomography data

3. Nonparametric functional calibration of computer models

4. Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems

5. Adaptive Numerical Designs for the Calibration of Computer Codes

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1. Parameter Inference Based on Gaussian Processes Informed by Nonlinear Partial Differential Equations;SIAM/ASA Journal on Uncertainty Quantification;2024-08-30

2. Efficient calibration of computer models with multivariate output;Journal of Multivariate Analysis;2024-07

3. Sequential design of multi-fidelity computer experiments with effect sparsity;Statistical Papers;2022-11-14

4. Fast L2 Calibration for Inexact Highway Traffic Flow Systems;Electronics;2022-11-12

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