Pages that link to "Item:Q630485"

The following pages link to Adaptive sparse polynomial chaos expansion based on least angle regression (Q630485):

Displaying 50 items.

• Imprecise random variables, random sets, and Monte Carlo simulation (Q324695) (← links)
• Practical application of the stochastic finite element method (Q338784) (← links)
• Quantifying initial and wind forcing uncertainties in the gulf of Mexico (Q341542) (← links)
• Selection of polynomial chaos bases via Bayesian model uncertainty methods with applications to sparse approximation of PDEs with stochastic inputs (Q348681) (← links)
• Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis (Q348759) (← links)
• A weighted \(\ell_1\)-minimization approach for sparse polynomial chaos expansions (Q349012) (← links)
• Compressive sampling of polynomial chaos expansions: convergence analysis and sampling strategies (Q349724) (← links)
• Analysis of discrete \(L^2\) projection on polynomial spaces with random evaluations (Q404295) (← links)
• Metamodelling with independent and dependent inputs (Q463030) (← links)
• A hybrid anchored-ANOVA - POD/Kriging method for uncertainty quantification in unsteady high-fidelity CFD simulations (Q525934) (← links)
• Non-intrusive uncertainty quantification using reduced cubature rules (Q680120) (← links)
• A robust and efficient stepwise regression method for building sparse polynomial chaos expansions (Q680129) (← links)
• Analysis of adaptive directional stratification for the controlled estimation of rare event probab\-ilities (Q693310) (← links)
• SAMBA: sparse approximation of moment-based arbitrary polynomial chaos (Q726888) (← links)
• Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions (Q727026) (← links)
• A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: applications to elliptic SPDEs (Q729029) (← links)
• A new surrogate modeling technique combining Kriging and polynomial chaos expansions - application to uncertainty analysis in computational dosimetry (Q729119) (← links)
• Enhancing \(\ell_1\)-minimization estimates of polynomial chaos expansions using basis selection (Q729190) (← links)
• Spectral likelihood expansions for Bayesian inference (Q729504) (← links)
• Sparse polynomial chaos expansions using variational relevance vector machines (Q781971) (← links)
• Treatment of multiple input uncertainties using the scaled boundary finite element method (Q821830) (← links)
• Active learning relevant vector machine for reliability analysis (Q822049) (← links)
• Sparse polynomial chaos expansions and adaptive stochastic finite elements using a regression approach (Q927907) (← links)
• An efficient non-intrusive reduced basis model for high dimensional stochastic problems in CFD (Q1647089) (← links)
• Efficient uncertainty quantification of stochastic CFD problems using sparse polynomial chaos and compressed sensing (Q1648406) (← links)
• Modelling uncertainty in incompressible flow simulation using Galerkin based generalized ANOVA (Q1682767) (← links)
• Uncertainty propagation of p-boxes using sparse polynomial chaos expansions (Q1685655) (← links)
• Nested polynomial trends for the improvement of Gaussian process-based predictors (Q1691892) (← links)
• A dynamical polynomial chaos approach for long-time evolution of SPDEs (Q1693454) (← links)
• Probabilistic robust design of control systems for high-fidelity cyber-physical testing (Q1737701) (← links)
• A critical appraisal of design of experiments for uncertainty quantification (Q1787391) (← links)
• Advanced kriging-based surrogate modelling and sensitivity analysis for rotordynamics with uncertainties (Q1982322) (← links)
• Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals (Q1985519) (← links)
• Sparse polynomial chaos expansions via compressed sensing and D-optimal design (Q1985532) (← links)
• Cost reduction of stochastic Galerkin method by adaptive identification of significant polynomial chaos bases for elliptic equations (Q1986283) (← links)
• A non-intrusive B-splines Bézier elements-based method for uncertainty propagation (Q1986828) (← links)
• A surrogate assisted adaptive framework for robust topology optimization (Q1986862) (← links)
• Systems of Gaussian process models for directed chains of solvers (Q1988026) (← links)
• An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework (Q1988073) (← links)
• An efficient adaptive forward-backward selection method for sparse polynomial chaos expansion (Q1988232) (← links)
• Model order reduction and low-dimensional representations for random linear dynamical systems (Q1996955) (← links)
• Model order reduction for random nonlinear dynamical systems and low-dimensional representations for their quantities of interest (Q1997672) (← links)
• Optimal Bayesian experimental design for subsurface flow problems (Q2020243) (← links)
• Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold (Q2020284) (← links)
• Efficient reliability analysis with a CDA-based dimension-reduction model and polynomial chaos expansion (Q2020745) (← links)
• A novel time-dependent system constraint boundary sampling technique for solving time-dependent reliability-based design optimization problems (Q2020916) (← links)
• Embedded ridge approximations (Q2020990) (← links)
• Data fusion for uncertainty quantification with non-intrusive polynomial chaos (Q2021255) (← links)
• A generalized multi-fidelity simulation method using sparse polynomial chaos expansion (Q2033075) (← links)
• Adaboost-based ensemble of polynomial chaos expansion with adaptive sampling (Q2060149) (← links)