Pages that link to "Item:Q1680850"
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The following pages link to Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions (Q1680850):
Displaying 12 items.
- Large scale variable fidelity surrogate modeling (Q1680849) (← links)
- A flexible polynomial expansion method for response analysis with random parameters (Q1723125) (← links)
- A comparison of two sampling methods for global sensitivity analysis (Q1948862) (← links)
- Risk of estimators for Sobol' sensitivity indices based on metamodels (Q2219226) (← links)
- Optimal space-filling design for symmetrical global sensitivity analysis of complex black-box models (Q2240294) (← links)
- A hybrid sequential sampling strategy for sparse polynomial chaos expansion based on compressive sampling and Bayesian experimental design (Q2246331) (← links)
- Parseval inequalities and lower bounds for variance-based sensitivity indices (Q2286373) (← links)
- Bayesian sparse polynomial chaos expansion for global sensitivity analysis (Q2309099) (← links)
- Symmetrical Design of Experiment in Global Sensitivity Analysis Based on ANOVA High-dimensional Model Representation (Q2809582) (← links)
- Design of Experiment in Global Sensitivity Analysis Based on ANOVA High-Dimensional Model Representation (Q3589996) (← links)
- An efficient local search-based genetic algorithm for constructing optimal Latin hypercube design (Q5059304) (← links)
- A sequential experimental design for multivariate sensitivity analysis using polynomial chaos expansion (Q5059412) (← links)
