Pages that link to "Item:Q2174145"
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The following pages link to Multi-level multi-fidelity sparse polynomial chaos expansion based on Gaussian process regression (Q2174145):
Displaying 14 items.
- Adaptive sparse polynomial chaos expansion based on least angle regression (Q630485) (← links)
- A generalized multi-fidelity simulation method using sparse polynomial chaos expansion (Q2033075) (← links)
- A multi-fidelity polynomial chaos-greedy Kaczmarz approach for resource-efficient uncertainty quantification on limited budget (Q2072434) (← links)
- Efficient uncertainty quantification of stochastic problems in CFD by combination of compressed sensing and POD-kriging (Q2156798) (← links)
- Stochastic field representation using bi-fidelity combination of proper orthogonal decomposition and kriging (Q2179204) (← links)
- Enhanced variable-fidelity surrogate-based optimization framework by Gaussian process regression and fuzzy clustering (Q2184447) (← links)
- Data-driven polynomial chaos expansion for machine learning regression (Q2220634) (← links)
- Efficient uncertainty quantification of CFD problems by combination of proper orthogonal decomposition and compressed sensing (Q2243373) (← links)
- An efficient multifidelity \(\ell_1\)-minimization method for sparse polynomial chaos (Q2310912) (← links)
- Multi-fidelity non-intrusive polynomial chaos based on regression (Q2419306) (← links)
- Stochastic analysis of structures under limited observations using kernel density estimation and arbitrary polynomial chaos expansion (Q2679444) (← links)
- A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms (Q6162876) (← links)
- Active learning-assisted multi-fidelity surrogate modeling based on geometric transformation (Q6550154) (← links)
- Active learning polynomial chaos expansion for reliability analysis by maximizing expected indicator function prediction error (Q6553474) (← links)
