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math.NA2018
Sparse Compression of Expected Solution Operators
Michael Feischl, Daniel Peterseim
We show that the expected solution operator of prototypical linear elliptic partial differential operators with random coefficients is well approximated by a computable sparse matr…
math.NA2018
Improved Efficiency of a Multi-Index FEM for Computational Uncertainty Quantification
Josef Dick, Michael Feischl, Christoph Schwab
We propose a multi-index algorithm for the Monte Carlo (MC) discretization of a linear, elliptic PDE with affine-parametric input. We prove an error vs. work analysis which allows…