Pages that link to "Item:Q944452"

The following pages link to Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations. Application to transport and continuum mechanics. (Q944452):

Displaying 50 items.

• A reduced basis approach for some weakly stochastic multiscale problems (Q1928185) (← links)
• Computational reduction for parametrized PDEs: strategies and applications (Q1932780) (← links)
• Reduced collocation methods: Reduced basis methods in the collocation framework (Q1955927) (← links)
• A reduced order model for a stable embedded boundary parametrized Cahn-Hilliard phase-field system based on cut finite elements (Q1983558) (← links)
• Local-global model reduction method for stochastic optimal control problems constrained by partial differential equations (Q1986266) (← links)
• An LP empirical quadrature procedure for reduced basis treatment of parametrized nonlinear PDEs (Q1986754) (← links)
• An adaptive local reduced basis method for solving PDEs with uncertain inputs and evaluating risk (Q1986786) (← links)
• A reduced basis approach for PDEs on parametrized geometries based on the shifted boundary finite element method and application to a Stokes flow (Q1987830) (← links)
• Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations (Q1987897) (← links)
• Solution of geometrically parametrised problems within a CAD environment via model order reduction (Q1989094) (← links)
• A two-step model order reduction method to simulate a compressible flow over an extended rough surface (Q1997115) (← links)
• Datadriven HOPGD based computational vademecum for welding parameter identification (Q1999553) (← links)
• A certified model reduction approach for robust parameter optimization with PDE constraints (Q2000521) (← links)
• Projection-based reduced order models for a cut finite element method in parametrized domains (Q2004559) (← links)
• Reduced basis decomposition: a certified and fast lossy data compression algorithm (Q2006533) (← links)
• Reduced basis method and domain decomposition for elliptic problems in networks and complex parametrized geometries (Q2006620) (← links)
• A hybrid model reduction method for stochastic parabolic optimal control problems (Q2020265) (← links)
• Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold (Q2020284) (← links)
• A staggered high-dimensional proper generalised decomposition for coupled magneto-mechanical problems with application to MRI scanners (Q2020286) (← links)
• A reduced-order shifted boundary method for parametrized incompressible Navier-Stokes equations (Q2020290) (← links)
• Hybridisable discontinuous Galerkin solution of geometrically parametrised Stokes flows (Q2021013) (← links)
• A globally convergent method to accelerate topology optimization using on-the-fly model reduction (Q2022073) (← links)
• A space-time certified reduced basis method for quasilinear parabolic partial differential equations (Q2044090) (← links)
• Numerical solution of the parametric diffusion equation by deep neural networks (Q2049099) (← links)
• Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories (Q2050562) (← links)
• Registration-based model reduction in complex two-dimensional geometries (Q2051104) (← links)
• Goal-oriented model reduction for parametrized time-dependent nonlinear partial differential equations (Q2060100) (← links)
• Urban planning image feature enhancement and simulation based on partial differential equation method (Q2064673) (← links)
• A reduced basis method for fractional diffusion operators. II (Q2070268) (← links)
• Reduced basis approximation and a posteriori error bounds for 4D-Var data assimilation (Q2071421) (← links)
• An approach for robust PDE-constrained optimization with application to shape optimization of electrical engines and of dynamic elastic structures under uncertainty (Q2071422) (← links)
• Projection-based model reduction of dynamical systems using space-time subspace and machine learning (Q2072456) (← links)
• Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: extension to geometrical parameterizations (Q2096859) (← links)
• Reduced-order modeling via proper generalized decomposition for uncertainty quantification of frequency response functions (Q2096868) (← links)
• A multiscale method for the heterogeneous Signorini problem (Q2114426) (← links)
• A theoretical analysis of deep neural networks and parametric PDEs (Q2117329) (← links)
• The DGDD method for reduced-order modeling of conservation laws (Q2124362) (← links)
• Windowed least-squares model reduction for dynamical systems (Q2127002) (← links)
• Non-intrusive model reduction of large-scale, nonlinear dynamical systems using deep learning (Q2127404) (← links)
• A POD-Galerkin reduced order model for a LES filtering approach (Q2131062) (← links)
• An EIM-degradation free reduced basis method via over collocation and residual hyper reduction-based error estimation (Q2132633) (← links)
• Registration-based model reduction of parameterized two-dimensional conservation laws (Q2135818) (← links)
• Automatic model order reduction for systems with frequency-dependent material properties (Q2145116) (← links)
• POD-Galerkin model order reduction for parametrized nonlinear time-dependent optimal flow control: an application to shallow water equations (Q2146441) (← links)
• A reduced order cut finite element method for geometrically parametrized steady and unsteady Navier-Stokes problems (Q2147279) (← links)
• Weakly-invasive Latin-PGD for solving time-dependent non-linear parametrized problems in solid mechanics (Q2156761) (← links)
• Efficient hyperreduction of high-order discontinuous Galerkin methods: element-wise and point-wise reduced quadrature formulations (Q2157120) (← links)
• A hyper-reduced MAC scheme for the parametric Stokes and Navier-Stokes equations (Q2157141) (← links)
• A multi-fidelity ensemble Kalman filter with hyperreduced reduced-order models (Q2160470) (← links)
• A deep learning based reduced order modeling for stochastic underground flow problems (Q2162031) (← links)