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On the convergence of adaptive stochastic collocation for elliptic partial differential equations with affine diffusion

Academic Article
Publication Date:
2022
abstract:
Convergence of an adaptive collocation method for the parametric stationary diffusion equation with finite-dimensional affine coefficient is shown. The adaptive algorithm relies on a recently introduced residual-based reliable a posteriori error estimator. For the convergence proof, a strategy recently used for a stochastic Galerkin method with a hierarchical error estimator is transferred to the collocation setting. Extensions to other variants of adaptive collocation methods (including the now classical approach proposed in [T. Gerstner and M. Griebel, Computing, 71 (2003), pp. 65-87]) are explored.
Iris type:
01.01 Articolo in rivista
Keywords:
adaptive algorithms; high-dimensional approximation; high-dimensional interpolation; parametric PDEs; random PDEs; sparse grids; stochastic collocation
List of contributors:
Tamellini, Lorenzo
Authors of the University:
TAMELLINI LORENZO
Handle:
https://iris.cnr.it/handle/20.500.14243/465041
Published in:
SIAM JOURNAL ON NUMERICAL ANALYSIS
Journal
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URL

https://epubs.siam.org/doi/10.1137/20M1364722
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