10 Model order reduction in uncertainty quantification
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Publication:4993251
DOI10.1515/9783110499001-010zbMath1470.37107OpenAlexW4245817722MaRDI QIDQ4993251
Publication date: 15 June 2021
Published in: Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/9783110499001-010
Numerical quadrature and cubature formulas (65D32) Large-scale systems (93A15) Numerical methods for ordinary differential equations (65L99) Approximation methods and numerical treatment of dynamical systems (37M99)
Cites Work
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- Evaluation of failure probability via surrogate models
- Numerical integration using sparse grids
- Certified reduced basis approximation for the coupling of viscous and inviscid parametrized flow models
- Model order reduction and low-dimensional representations for random linear dynamical systems
- Model order reduction for random nonlinear dynamical systems and low-dimensional representations for their quantities of interest
- Stochastic collocation and stochastic Galerkin methods for linear differential algebraic equations
- Parametric modeling and model order reduction for (electro-)thermal analysis of nanoelectronic structures
- A Hankel norm for quadrature rules solving random linear dynamical systems
- Dimension reduction of large-scale systems. Proceedings of a workshop, Oberwolfach, Germany, October 19--25, 2003.
- A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
- On the convergence of generalized polynomial chaos expansions
- Introduction to Uncertainty Quantification
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- Eigenvalues of the Jacobian of a Galerkin-Projected Uncertain ODE System
- POLYNOMIAL CHAOS FOR LINEAR DIFFERENTIAL ALGEBRAIC EQUATIONS WITH RANDOM PARAMETERS
- Polynomial chaos for the approximation of uncertainties: Chances and limits
- A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data
- Model reduction methods based on Krylov subspaces
- Model Order Reduction for Differential-Algebraic Equations: A Survey
- $\mathcal H_2$-Quasi-Optimal Model Order Reduction for Quadratic-Bilinear Control Systems
- Model Order Reduction for Stochastic Expansions of Electric Circuits
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- STOCHASTIC GALERKIN METHODS AND MODEL ORDER REDUCTION FOR LINEAR DYNAMICAL SYSTEMS
- FAST AND ACCURATE MODEL REDUCTION FOR SPECTRAL METHODS IN UNCERTAINTY QUANTIFICATION
- Stability Preservation in Stochastic Galerkin Projections of Dynamical Systems
- Nonintrusive Polynomial Chaos Expansions for Sensitivity Analysis in Stochastic Differential Equations
- Efficient greedy algorithms for high-dimensional parameter spaces with applications to empirical interpolation and reduced basis methods
- Approximation of Large-Scale Dynamical Systems
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