8 citations · 9 across the 2 of their papers we have counts for
4 papers
Post-Processing of High-Dimensional Data
Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko +2
Scientific computations or measurements may result in huge volumes of data. Often these can be thought of representing a real-valued function on a high-dimensional domain, and can…
Bayesian Parameter Estimation via Filtering and Functional Approximations
Hermann G. Matthies, Alexander Litvinenko, Bojana V. Rosic +1
The inverse problem of determining parameters in a model by comparing some output of the model with observations is addressed. This is a description for what hat to be done to use…
Parameter Estimation via Conditional Expectation --- A Bayesian Inversion
Hermann G. Matthies, Elmar Zander, Bojana Rosic +1
When a mathematical or computational model is used to analyse some system, it is usual that some parameters resp.\ functions or fields in the model are not known, and hence uncerta…
Inverse Problems in a Bayesian Setting
Hermann G. Matthies, Elmar Zander, Bojana V. Rosić +2
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) --- the propagation of uncertainty through a computational (forward) model --- are strongly connected. I…