Publications associées à Quantitative $ L ^{ 2 } $ Error Analysis for Interpolation Methods and Wavelet Expansions

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Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

Quantitative $ L ^{ 2 } $ Error Analysis for Interpolation Methods and Wavelet Expansions

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Retraction-based numerical methods for continuation, interpolation and time integration on manifolds

Plug-and-play adaptive surrogate modeling of parametric nonlinear dynamics in frequency domain

Perturbed Fourier uniqueness and interpolation results in higher dimensions

Functional Tucker Approximation Using Chebyshev Interpolation

MATHICSE Technical Report : Frequency-domain non-intrusive greedy Model Order Reduction based on minimal rational approximation

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Regularity results for rough solutions of the incompressible Euler equations via interpolation methods

Low-rank tensor methods for large Markov chains and forward feature selection methods

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source

Plug-and-play adaptive surrogate modeling of parametric nonlinear dynamics in frequency domain

Retraction-based numerical methods for continuation, interpolation and time integration on manifolds

Perturbed Fourier uniqueness and interpolation results in higher dimensions

Functional Tucker Approximation Using Chebyshev Interpolation

Regularity results for rough solutions of the incompressible Euler equations via interpolation methods

Low-rank tensor methods for large Markov chains and forward feature selection methods

MATHICSE Technical Report : Frequency-domain non-intrusive greedy Model Order Reduction based on minimal rational approximation

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Attributing Aliasing Artifacts in Dirty Intensity Fields to their Parent Source