We introduce a general a priori convergence result for the approximation of parametric derivatives of parametrized functions. We consider the best approximations to parametric derivatives in a sequence of approximation spaces generated by a general approximation scheme, and we show that these approximations are convergent provided that the best approximation to the function itself is convergent. We also provide estimates for the convergence rates. We present numerical results with spaces generated by a particular approximation scheme—the Empirical Interpolation Method—to confirm the validity of the general theory
Abstract: The authors construct some extended interpolation formulae to approximate the derivatives ...
Parametrized families of PDEs arise in various contexts suchas inverse problems, control and optimiz...
We extend the classical empirical interpolation method [M. Barrault, Y. Maday, N.C. Nguyen...
Received *****; accepted after revision +++++ Presented by We present rigorous a posteriori error bo...
We present rigorous a posteriori error bounds for the Empirical Interpolation Method (EIM). The esse...
We present rigorous a posteriori error bounds for the Empirical Interpolation Method (EIM). The esse...
We extend the classical empirical interpolation method [1] to a weighted empirical interpolation met...
We derive analyticity criteria for explicit error bounds and an exponential rate of convergence of t...
We extend the classical empirical interpolation method [M. Barrault, Y. Maday, N.C. Nguyen and A.T. ...
The empirical interpolation method is an interpolation scheme with problem dependent basis functions...
Abstract. The Generalized Empirical Interpolation Method (GEIM, [12]) is an extension first presente...
International audienceLet $F$ be a compact set of a Banach space $\mathcal{X}$. This paper analyses ...
The authors construct some extended interpolation formulae to approximate the derivatives of a func...
International audienceIn an effort to extend the classical lagrangian interpolation tools, new inter...
The 10th International Conference on Sampling Theory and Applications (SampTA) took place from July ...
Abstract: The authors construct some extended interpolation formulae to approximate the derivatives ...
Parametrized families of PDEs arise in various contexts suchas inverse problems, control and optimiz...
We extend the classical empirical interpolation method [M. Barrault, Y. Maday, N.C. Nguyen...
Received *****; accepted after revision +++++ Presented by We present rigorous a posteriori error bo...
We present rigorous a posteriori error bounds for the Empirical Interpolation Method (EIM). The esse...
We present rigorous a posteriori error bounds for the Empirical Interpolation Method (EIM). The esse...
We extend the classical empirical interpolation method [1] to a weighted empirical interpolation met...
We derive analyticity criteria for explicit error bounds and an exponential rate of convergence of t...
We extend the classical empirical interpolation method [M. Barrault, Y. Maday, N.C. Nguyen and A.T. ...
The empirical interpolation method is an interpolation scheme with problem dependent basis functions...
Abstract. The Generalized Empirical Interpolation Method (GEIM, [12]) is an extension first presente...
International audienceLet $F$ be a compact set of a Banach space $\mathcal{X}$. This paper analyses ...
The authors construct some extended interpolation formulae to approximate the derivatives of a func...
International audienceIn an effort to extend the classical lagrangian interpolation tools, new inter...
The 10th International Conference on Sampling Theory and Applications (SampTA) took place from July ...
Abstract: The authors construct some extended interpolation formulae to approximate the derivatives ...
Parametrized families of PDEs arise in various contexts suchas inverse problems, control and optimiz...
We extend the classical empirical interpolation method [M. Barrault, Y. Maday, N.C. Nguyen...