State estimation in nonlinear parametric time dependent systems using tensor train

Cites Work

Tensor-Train Decomposition
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Reduced order modeling based on POD of a parabolized Navier-Stokes equations model II: trust region POD 4D VAR data assimilation
State observers of a vascular fluid-structure interaction model through measurements in the solid
Bounds for eigenvalues using traces
Parameterised non-intrusive reduced order methods for ensemble Kalman filter data assimilation
A tensor network Kalman filter with an application in recursive MIMO Volterra system identification
A tensor-train accelerated solver for integral equations in complex geometries
A low-rank approach to the solution of weak constraint variational data assimilation problems
A continuous analogue of the tensor-train decomposition
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3D-VAR for parameterized partial differential equations: a certified reduced basis approach
A non-linear observer for unsteady three-dimensional flows
PBDW State Estimation: Noisy Observations; Configuration-Adaptive Background Spaces; Physical Interpretations
Adaptive Low-Rank Methods: Problems on Sobolev Spaces
Spectral Tensor-Train Decomposition
Polynomial Chaos Expansion of Random Coefficients and the Solution of Stochastic Partial Differential Equations in the Tensor Train Format
A POD reduced-order 4D-Var adaptive mesh ocean modelling approach
An Adaptive Parametrized-Background Data-Weak approach to variational data assimilation
Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter
Low rank updates in preconditioning the saddle point systems arising from data assimilation problems
Greedy Algorithms for Optimal Measurements Selection in State Estimation Using Reduced Models
Fast Solution of Parabolic Problems in the Tensor Train/Quantized Tensor Train Format with Initial Application to the Fokker--Planck Equation
A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates
A Time-Dependent Parametrized Background Data-Weak Approach
Adaptive PBDW Approach to State Estimation: Noisy Observations; User-Defined Update Spaces
Data Assimilation in Reduced Modeling
A discrete-time optimal filtering approach for non-linear systems as a stable discretization of the Mortensen observer
Bayesian inversion for electromyography using low-rank tensor formats
Data Assimilation
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