Predicting the output from a complex computer code when fast approximations are available
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Summary
The purpose of the current paper is to explore ways in which runs from several levels of a code can be used to make inference about the output from the most complex code.
- Type
- article
- Published
- 2000-03-01
- Cited by
- 1,695
- References
- 18
- OpenAlex
- https://openalex.org/W1977046327
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:119357596
Keywords
Code (set theory), Mathematics, Volume (thermodynamics), Algorithm, Computer science
References
- Bayesian numerical analysis
- Simplicity out of complexity
- A Bayesian approach to model inadequacy for polynomial regression
- Bayesian design and analysis of computer experiments: Use of derivatives in surface prediction
- Metric spaces and completely monotone functions
- Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer Experiments
- Circuit optimization via sequential computer experiments: design of an output buffer
- Screening, predicting, and computer experiments
- Robust estimation of the variogram: I
- Bayes–Hermite quadrature
- Simplicity out of complexity in environmental modelling: Occam's razor revisited.
- Curve Fitting and Optimal Design for Prediction
- Bayesian Numerical Analysis
- Design and analysis of computer experiments
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- Predictive Maturity of Computer Models Using Functional and Multivariate Output
- Motivated Metamodels: Synthesis of Cause-Effect Reasoning and Statistical Metamodeling
- Prediction and Calibration Using Outputs from Multiple Computer Simulators
- Statistical Inference Utilizing Agent Based Models
- Efficient Characterization of Structural Dynamic Responses under Uncertainties: from Order-Reduced Simulation to Data-Driven Emulation
- Construction of some new families of nested orthogonal arrays
- Sequential design of computer experiments to minimize integrated response functions
- Méthodes d'interpolation à noyaux pour l'approximation de fonctions type boîte noire coûteuses
- Nested Lattice Sampling: A New Sampling Scheme Derived by Randomizing Nested Orthogonal Arrays
- An Iterative Uncertainty Assessment Technique for Environmental Modeling
- Predictive quantification of surrogate model fidelity based on modal variations with sample density
- Penetrator reliability investigation and design exploration : from conventional design processes to innovative uncertainty-capturing algorithms.
- Simplified Cross-Correlation Estimation For Multi-Fidelity Surrogate Cokriging Models
- Verification and Validation under Uncertainty Applied to Finite Element Models of Historic Masonry Monuments
- Development of Multidisciplinary, Multifidelity Analysis, Integration, and Optimization of Aerospace Vehicles
- Policy making using computer simulators for complex physical systems : Bayesian decision support for the development of adaptive strategies
- Multi-fidelity Gaussian process regression for computer experiments
- Inverse problems occurring in uncertainty analysis
- Multifidelity Analysis and Optimization for Supersonic Design
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