102 citations · 352 across the 27 of their papers we have counts for
3 papers · 1 filter
Inverse problems and uncertainty quantification
Alexander Litvinenko, Hermann G. Matthies
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) model - are strongly connected. In th…
To be or not to be intrusive? The solution of parametric and stochastic equations - the "plain vanilla" Galerkin case
Loïc Giraldi, Alexander Litvinenko, Dishi Liu +2
In parametric equations - stochastic equations are a special case - one may want to approximate the solution such that it is easy to evaluate its dependence of the parameters. Inte…
Partitioned treatment of uncertainty in coupled domain problems: A separated representation approach
Mohammad Hadigol, Alireza Doostan, Hermann G. Matthies +1
This work is concerned with the propagation of uncertainty across coupled domain problems with high-dimensional random inputs. A stochastic model reduction approach based on low-ra…