Pages that link to "Item:Q1691775"

The following pages link to Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction (Q1691775):

Displaying 49 items.

• Efficient non linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations (Q2880241) (← links)
• Sparse reduced-order modelling: sensor-based dynamics to full-state estimation (Q4563901) (← links)
• Data-Driven Filtered Reduced Order Modeling of Fluid Flows (Q4568096) (← links)
• Online Interpolation Point Refinement for Reduced-Order Models using a Genetic Algorithm (Q4603498) (← links)
• Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems (Q4636377) (← links)
• Leveraging Sparsity and Compressive Sensing for Reduced Order Modeling (Q4637167) (← links)
• Space--Time Least-Squares Petrov--Galerkin Projection for Nonlinear Model Reduction (Q4646450) (← links)
• 6 Model reduction in computational aerodynamics (Q4993247) (← links)
• 9 From the POD-Galerkin method to sparse manifold models (Q4993250) (← links)
• Projection-based model reduction with dynamically transformed modes (Q4994009) (← links)
• A Least-Squares Finite Element Reduced Basis Method (Q4997358) (← links)
• Model-Based Adaptive MOR Framework for Unsteady Flows Around Lifting Bodies (Q5014030) (← links)
• Application of physics-constrained data-driven reduced-order models to shape optimization (Q5022975) (← links)
• Fourier Collocation and Reduced Basis Methods for Fast Modeling of Compressible Flows (Q5042004) (← links)
• SNS: A Solution-Based Nonlinear Subspace Method for Time-Dependent Model Order Reduction (Q5112544) (← links)
• Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference (Q5146677) (← links)
• Constrained sparse Galerkin regression (Q5226317) (← links)
• Data-Driven Time Parallelism via Forecasting (Q5230597) (← links)
• On the role of nonlinear correlations in reduced-order modelling (Q5863430) (← links)
• Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder (Q5886859) (← links)
• Preconditioned least‐squares Petrov–Galerkin reduced order models (Q6071434) (← links)
• Localized model order reduction and domain decomposition methods for coupled heterogeneous systems (Q6082575) (← links)
• Hyper-reduction for Petrov-Galerkin reduced order models (Q6084430) (← links)
• Reduced order modeling of parametrized pulsatile blood flows: hematocrit percentage and heart rate (Q6085392) (← links)
• Challenges of order reduction techniques for problems involving polymorphic uncertainty (Q6088632) (← links)
• Consistency of the full and reduced order models for evolve‐filter‐relax regularization of convection‐dominated, marginally‐resolved flows (Q6090729) (← links)
• Non‐intrusive reduced‐order modeling using convolutional autoencoders (Q6092270) (← links)
• CD-ROM: complemented deep -- reduced order model (Q6094649) (← links)
• Predictive reduced order modeling of chaotic multi-scale problems using adaptively sampled projections (Q6095092) (← links)
• On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows (Q6095138) (← links)
• Physics Guided Machine Learning for Variational Multiscale Reduced Order Modeling (Q6097872) (← links)
• Evaluation of dual-weighted residual and machine learning error estimation for projection-based reduced-order models of steady partial differential equations (Q6101904) (← links)
• \textit{FastSVD-ML-ROM}: a reduced-order modeling framework based on machine learning for real-time applications (Q6116133) (← links)
• A multifidelity deep operator network approach to closure for multiscale systems (Q6116145) (← links)
• Space-Time Reduced Basis Methods for Parametrized Unsteady Stokes Equations (Q6194969) (← links)
• Energy-conserving hyper-reduction and temporal localization for reduced order models of the incompressible Navier-Stokes equations (Q6196594) (← links)
• Registration-based model reduction of parameterized PDEs with spatio-parameter adaptivity (Q6196631) (← links)
• Projection-based reduced order modeling and data-driven artificial viscosity closures for incompressible fluid flows (Q6497167) (← links)
• Fluid-reduced-solid interaction (FrSI): physics- and projection-based model reduction for cardiovascular applications (Q6498462) (← links)
• An adaptive sampling algorithm for reduced-order models using isomap (Q6499911) (← links)
• Adaptive greedy algorithms based on parameter-domain decomposition and reconstruction for the reduced basis method (Q6554352) (← links)
• Randomized low-rank approximation methods for projection-based model order reduction of large nonlinear dynamical problems (Q6555374) (← links)
• Preserving general physical properties in model reduction of dynamical systems via constrained-optimization projection (Q6555513) (← links)
• Error modeling for surrogates of dynamical systems using machine learning (Q6557511) (← links)
• An adaptive, training-free reduced-order model for convection-dominated problems based on hybrid snapshots (Q6574153) (← links)
• A hybrid numerical methodology coupling reduced order modeling and graph neural networks for non-parametric geometries: applications to structural dynamics problems (Q6595908) (← links)
• Machine learning methods for reduced order modeling (Q6629175) (← links)
• A data-driven reduced-order modeling approach for parameterized time-domain Maxwell's equations (Q6647127) (← links)
• Parametric model reduction with convolutional neural networks (Q6648521) (← links)