Pages that link to "Item:Q2952135"

The following pages link to Nonlinear model order reduction based on local reduced-order bases (Q2952135):

Displaying 50 items.

• An iterative algorithm for POD basis adaptation in solving parametric convection-diffusion equations (Q2670330) (← links)
• A reduced order modeling method based on GNAT-embedded hybrid snapshot simulation (Q2672356) (← links)
• Quadratic approximation manifold for mitigating the Kolmogorov barrier in nonlinear projection-based model order reduction (Q2672789) (← links)
• Robust and globally efficient reduction of parametric, highly nonlinear computational models and real time online performance (Q2674110) (← links)
• A DEIM driven reduced basis method for the diffuse Stokes/Darcy model coupled at parametric phase-field interfaces (Q2677375) (← links)
• Reprint of: Robust and globally efficient reduction of parametric, highly nonlinear computational models and real time online performance (Q2679338) (← links)
• Operator inference for non-intrusive model reduction with quadratic manifolds (Q2679511) (← links)
• Model reduction for the material point method via an implicit neural representation of the deformation map (Q2687512) (← links)
• Certified reduced order method for the parametrized Allen-Cahn equation (Q2697785) (← links)
• Energy stable model reduction of neurons by nonnegative discrete empirical interpolation (Q2800440) (← links)
• A survey of projection-based model reduction methods for parametric dynamical systems (Q2808259) (← links)
• Sparse sensor placement optimization for classification (Q2829445) (← links)
• A POD–EIM reduced two-scale model for precipitation in porous media (Q2831100) (← links)
• Efficient non linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations (Q2880241) (← links)
• Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates (Q2947046) (← links)
• A multiscale large time increment/FAS algorithm with time-space model reduction for frictional contact problems (Q2952404) (← links)
• Dimensional reduction of nonlinear finite element dynamic models with finite rotations and energy-based mesh sampling and weighting for computational efficiency (Q2952487) (← links)
• Improving the efficiency of large scale topology optimization through on-the-fly reduced order model construction (Q2952629) (← links)
• Data-driven model reduction for the Bayesian solution of inverse problems (Q2952708) (← links)
• Structure-preserving, stability, and accuracy properties of the energy-conserving sampling and weighting method for the hyper reduction of nonlinear finite element dynamic models (Q2952713) (← links)
• Adaptive<i>h</i>-refinement for reduced-order models (Q2952718) (← links)
• An adaptive and efficient greedy procedure for the optimal training of parametric reduced-order models (Q2952722) (← links)
• Adaptive training of local reduced bases for unsteady incompressible Navier-Stokes flows (Q2952765) (← links)
• Nonlinear model reduction via a locally weighted POD method (Q2952890) (← links)
• Projection‐based model reduction for contact problems (Q2952907) (← links)
• Optimal Reduced Model Algorithms for Data-Based State Estimation (Q3386988) (← links)
• Nonlinear model reduction based on the finite element method with interpolated coefficients: Semilinear parabolic equations (Q3459237) (← links)
• Geometric Subspace Updates with Applications to Online Adaptive Nonlinear Model Reduction (Q4604565) (← links)
• Reduced Basis Methods for Uncertainty Quantification (Q4636408) (← links)
• An Adaptive Way of Choosing Significant Snapshots for Proper Orthogonal Decomposition (Q4973304) (← links)
• Reduced-Order Modeling Based on Hybrid Snapshot Simulation (Q4987345) (← links)
• 8 Reduced-order modeling for applications to the cardiovascular system (Q4993249) (← links)
• Nonlinear model reduction on metric spaces. Application to one-dimensional conservative PDEs in Wasserstein spaces (Q4994014) (← links)
• A POD-based reduced-order model for uncertainty analyses in shallow water flows (Q5031503) (← links)
• Interpolation-based reduced-order modelling for steady transonic flows via manifold learning (Q5071728) (← links)
• State Estimation with Model Reduction and Shape Variability. Application to biomedical problems (Q5088772) (← links)
• Piecewise-Global Nonlinear Model Order Reduction for PDE-Constrained Optimization in High-Dimensional Parameter Spaces (Q5095491) (← links)
• Leveraging reduced-order models for state estimation using deep learning (Q5113091) (← links)
• Learning the tangent space of dynamical instabilities from data (Q5205672) (← links)
• Failure Probability Estimation of Linear Time Varying Systems by Progressive Refinement of Reduced Order Models (Q5237184) (← links)
• Model order reduction using sparse coding exemplified for the lid-driven cavity (Q5360539) (← links)
• Nonlinear Reduced Models for State and Parameter Estimation (Q5862904) (← links)
• Numerical Assessment of a Nonintrusive Surrogate Model Based on Recurrent Neural Networks and Proper Orthogonal Decomposition: Rayleigh–Bénard Convection (Q5880415) (← links)
• Learning physics-based models from data: perspectives from inverse problems and model reduction (Q5887831) (← links)
• Reduced basis methods for time-dependent problems (Q5887836) (← links)
• A localized reduced basis approach for unfitted domain methods on parameterized geometries (Q6048372) (← links)
• Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression (Q6048987) (← links)
• Neural-network-augmented projection-based model order reduction for mitigating the Kolmogorov barrier to reducibility (Q6054198) (← links)
• Adaptive experimental design for multi‐fidelity surrogate modeling of multi‐disciplinary systems (Q6069984) (← links)
• Space‐local reduced‐order bases for accelerating reduced‐order models through sparsity (Q6071407) (← links)