Efficient quadratures for high-dimensional Bayesian data assimilation

Numerical approximation and computational geometry (primarily algorithms) (65Dxx) Probabilistic methods, stochastic differential equations (65Cxx) Approximations and expansions (41Axx)

Cites Work

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Tensor-Train Decomposition
Multimodal ensemble Kalman filtering using Gaussian mixture models
Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids
On the convergence of the ensemble Kalman filter.
Numerical integration using sparse grids
Explicit cost bounds of algorithms for multivariate tensor product problems
Tempered particle filtering
High dimensional polynomial interpolation on sparse grids
Information geometry of physics-informed statistical manifolds and its use in data assimilation
Generation of nested quadrature rules for generic weight functions via numerical optimization: application to sparse grids
Sparse-grid, reduced-basis Bayesian inversion: nonaffine-parametric nonlinear equations
Spectral Tensor-Train Decomposition
Numerical Integration in Multiple Dimensions with Designed Quadrature
Approximation Results for Orthogonal Polynomials in Sobolev Spaces
Properties of Some Weighted Sobolev Spaces and Application to Spectral Approximations
On Generating Orthogonal Polynomials
Turbulent Flows
Coupling Techniques for Nonlinear Ensemble Filtering
Grid methods for Bayes-optimal continuous-discrete filtering and utilizing a functional tensor train representation
Data-Informed Method of Distributions for Hyperbolic Conservation Laws
Data Assimilation
The ensemble Kalman filter for combined state and parameter estimation
Is Gauss Quadrature Better than Clenshaw–Curtis?
State estimation in nonlinear parametric time dependent systems using tensor train

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