Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models
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Publication:6631188
DOI10.1080/00401706.2023.2246157MaRDI QIDQ6631188
Stefan M. Wild, Matthew Plumlee, Author name not available (Why is that?)
Publication date: 31 October 2024
Published in: Technometrics (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- BART: Bayesian additive regression trees
- Scaled Gaussian Stochastic Process for Computer Model Calibration and Prediction
- Approximate Bayesian computational methods
- Computational intelligence in expensive optimization problems
- Bayes-Hermite quadrature
- Efficient global optimization of expensive black-box functions
- The design and analysis of computer experiments
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- Bayesian calibration of computer models. (With discussion)
- Computer Model Calibration Using High-Dimensional Output
- Adaptive Numerical Designs for the Calibration of Computer Codes
- Combining Field Data and Computer Simulations for Calibration and Prediction
- Modularization in Bayesian analysis, with emphasis on analysis of computer models
- On-site surrogates for large-scale calibration
- Replication or Exploration? Sequential Design for Stochastic Simulation Experiments
- Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs
- Active Learning for Deep Gaussian Process Surrogates
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