The following pages link to redbKIT (Q24900):
Displaying 50 items.
- Sampling-free model reduction of systems with low-rank parameterization (Q2026127) (← links)
- Application of adaptive ANOVA and reduced basis methods to the stochastic Stokes-Brinkman problem (Q2027195) (← links)
- A space-time certified reduced basis method for quasilinear parabolic partial differential equations (Q2044090) (← links)
- Shape holomorphy of the Calderón projector for the Laplacian in \(\mathbb{R}^2\) (Q2044585) (← links)
- Numerical solution of the parametric diffusion equation by deep neural networks (Q2049099) (← links)
- A model reduction approach for inverse problems with operator valued data (Q2049926) (← links)
- Model reduction and neural networks for parametric PDEs (Q2050400) (← links)
- Registration-based model reduction in complex two-dimensional geometries (Q2051104) (← links)
- Low-rank dynamic mode decomposition: an exact and tractable solution (Q2062877) (← links)
- An efficient iterative method for solving parameter-dependent and random convection-diffusion problems (Q2067305) (← links)
- A reduced basis method for fractional diffusion operators. II (Q2070268) (← links)
- Multi-fidelity regression using artificial neural networks: efficient approximation of parameter-dependent output quantities (Q2072477) (← links)
- Stabilized reduced-order models for unsteady incompressible flows in three-dimensional parametrized domains (Q2084084) (← links)
- Mapping of coherent structures in parameterized flows by learning optimal transportation with Gaussian models (Q2088388) (← links)
- A POD-based ROM strategy for the prediction in time of advection-dominated problems (Q2088390) (← links)
- Full and reduced order model consistency of the nonlinearity discretization in incompressible flows (Q2096852) (← links)
- Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: extension to geometrical parameterizations (Q2096859) (← links)
- Isogeometric analysis of acoustic scattering with perfectly matched layers (IGAPML) (Q2096874) (← links)
- Long-time Reynolds averaging of reduced order models for fluid flows: Preliminary results (Q2099367) (← links)
- Verifiability of the data-driven variational multiscale reduced order model (Q2103423) (← links)
- Deep-HyROMnet: a deep learning-based operator approximation for hyper-reduction of nonlinear parametrized PDEs (Q2103427) (← links)
- Solving parametric partial differential equations with deep rectified quadratic unit neural networks (Q2103467) (← links)
- A reduced-order extrapolating collocation spectral method based on POD for the 2D Sobolev equations (Q2108272) (← links)
- A reduced basis method for radiative transfer equation (Q2113644) (← links)
- Data-driven modeling of linear dynamical systems with quadratic output in the AAA framework (Q2113660) (← links)
- A theoretical analysis of deep neural networks and parametric PDEs (Q2117329) (← links)
- Model reduction for fractional elliptic problems using Kato's formula (Q2119432) (← links)
- Non-linearly stable reduced-order models for incompressible flow with energy-conserving finite volume methods (Q2123750) (← links)
- Efficient estimation of cardiac conductivities: a proper generalized decomposition approach (Q2123851) (← links)
- A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables (Q2124009) (← links)
- Data-driven modeling of two-dimensional detonation wave fronts (Q2124122) (← links)
- The reduced-dimension technique for the unknown solution coefficient vectors in the Crank-Nicolson finite element method for the Sobolev equation (Q2124695) (← links)
- Linear/ridge expansions: enhancing linear approximations by ridge functions (Q2124754) (← links)
- A greedy non-intrusive reduced order model for shallow water equations (Q2129263) (← 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)
- Physics-informed machine learning for reduced-order modeling of nonlinear problems (Q2133556) (← links)
- A reduced order method for nonlinear parameterized partial differential equations using dynamic mode decomposition coupled with \(k\)-nearest-neighbors regression (Q2133585) (← links)
- Machine learning and reduced order computation of a friction stir welding model (Q2133689) (← links)
- Enforcing exact physics in scientific machine learning: a data-driven exterior calculus on graphs (Q2133772) (← links)
- The reduced-order method of continuous space-time finite element scheme for the non-stationary incompressible flows (Q2133804) (← links)
- Registration-based model reduction of parameterized two-dimensional conservation laws (Q2135818) (← links)
- The neural network shifted-proper orthogonal decomposition: a machine learning approach for non-linear reduction of hyperbolic equations (Q2138717) (← links)
- A machine learning method for real-time numerical simulations of cardiac electromechanics (Q2138843) (← links)
- A reduced order extrapolating technique of solution coefficient vectors to collocation spectral method for telegraph equation (Q2144077) (← links)
- Automatic model order reduction for systems with frequency-dependent material properties (Q2145116) (← links)
- A reduced order cut finite element method for geometrically parametrized steady and unsteady Navier-Stokes problems (Q2147279) (← links)
- An adaptive data-driven reduced order model based on higher order dynamic mode decomposition (Q2149050) (← links)
- A non-intrusive neural network model order reduction algorithm for parameterized parabolic PDEs (Q2159858) (← links)
- Retracted: Model order reduction method based on machine learning for parameterized time-dependent partial differential equations (Q2161825) (← links)
