Pages that link to "Item:Q4785938"

The following pages link to The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (Q4785938):

Displaying 50 items.

• Computational uncertainty analysis in multiresolution materials via stochastic constitutive theory (Q643960) (← links)
• Stochastic elastic-plastic finite elements (Q646317) (← links)
• Recursive maximum likelihood parameter estimation for state space systems using polynomial chaos theory (Q646428) (← links)
• Solving elliptic problems with non-Gaussian spatially-dependent random coefficients (Q649448) (← links)
• An alternative unsteady adaptive stochastic finite element formulation based on interpolation at constant phase (Q653649) (← links)
• A reduced spectral function approach for the stochastic finite element analysis (Q653731) (← links)
• Kernel principal component analysis for stochastic input model generation (Q655052) (← links)
• A dynamically adaptive wavelet approach to stochastic computations based on polynomial chaos -- capturing all scales of random modes on independent grids (Q655055) (← links)
• The stochastic finite element method: past, present and future (Q658211) (← links)
• Geometrically nonlinear behavior of structural systems with random material property: an asymptotic spectral stochastic approach (Q658307) (← links)
• Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data (Q658826) (← links)
• Stochastic computation based on orthogonal expansion of random fields (Q660280) (← links)
• Uncertainty quantification of MEMS using a data-dependent adaptive stochastic collocation method (Q660314) (← links)
• A reduced basis approach for variational problems with stochastic parameters: application to heat conduction with variable Robin coefficient (Q660371) (← links)
• Solution of stochastic nonlinear time fractional PDEs using polynomial chaos expansion combined with an exponential integrator (Q666765) (← links)
• A stochastic Galerkin approach to uncertainty quantification in poroelastic media (Q669364) (← links)
• Approximate methods for stochastic eigenvalue problems (Q669769) (← links)
• A robust and efficient stepwise regression method for building sparse polynomial chaos expansions (Q680129) (← links)
• Dependence of polynomial chaos on random types of forces of KdV equations (Q693397) (← links)
• Bayesian inference with optimal maps (Q695159) (← links)
• Simplified CSP analysis of a stiff stochastic ODE system (Q695820) (← links)
• Hybrid perturbation-polynomial chaos approaches to the random algebraic eigenvalue problem (Q695824) (← links)
• Sparse pseudospectral approximation method (Q695891) (← links)
• Constrained probabilistic collocation method for uncertainty quantification of geophysical models (Q723112) (← links)
• SAMBA: sparse approximation of moment-based arbitrary polynomial chaos (Q726888) (← links)
• Gaussian processes with built-in dimensionality reduction: applications to high-dimensional uncertainty propagation (Q726924) (← links)
• Stabilized FE simulation of prototype thermal-hydraulics problems with integrated adjoint-based capabilities (Q726936) (← links)
• Polynomial meta-models with canonical low-rank approximations: numerical insights and comparison to sparse polynomial chaos expansions (Q727026) (← links)
• Long-time uncertainty propagation using generalized polynomial chaos and flow map composition (Q728699) (← links)
• A heterogeneous stochastic FEM framework for elliptic PDEs (Q728826) (← links)
• Variance reduction through robust design of boundary conditions for stochastic hyperbolic systems of equations (Q728842) (← links)
• Uncertainty propagation using infinite mixture of gaussian processes and variational Bayesian inference (Q729001) (← 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)
• Asymptotic-preserving methods for hyperbolic and transport equations with random inputs and diffusive scalings (Q729189) (← links)
• Enhancing \(\ell_1\)-minimization estimates of polynomial chaos expansions using basis selection (Q729190) (← links)
• A well-posed and stable stochastic Galerkin formulation of the incompressible Navier-Stokes equations with random data (Q729316) (← links)
• Enhancing sparsity of Hermite polynomial expansions by iterative rotations (Q729367) (← links)
• Spectral likelihood expansions for Bayesian inference (Q729504) (← links)
• A two-level stochastic collocation method for semilinear elliptic equations with random coefficients (Q729862) (← links)
• A domain adaptive stochastic collocation approach for analysis of MEMS under uncertainties (Q733023) (← links)
• Towards essential improvement for the parareal-TR and parareal-Gauss4 algorithms (Q738990) (← links)
• A reduced polynomial chaos expansion method for the stochastic finite element analysis (Q746416) (← links)
• Data-based importance sampling estimates for extreme events (Q776693) (← links)
• Rank adaptive tensor recovery based model reduction for partial differential equations with high-dimensional random inputs (Q778295) (← links)
• Analysis of methods for the Maxwell-random Lorentz model (Q780020) (← links)
• Learning constitutive relations from indirect observations using deep neural networks (Q781968) (← links)
• Sparse polynomial chaos expansions using variational relevance vector machines (Q781971) (← links)
• ANOVA Gaussian process modeling for high-dimensional stochastic computational models (Q781984) (← links)
• Gaussian process regression and conditional polynomial chaos for parameter estimation (Q781985) (← links)