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Oberwolfach Reports

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Volume 16, Issue 1, 2019, pp. 695–772
DOI: 10.4171/OWR/2019/12

Published online: 2020-02-26

Uncertainty Quantification

Oliver Ernst[1], Fabio Nobile[2], Claudia Schillings[3] and Tim Sullivan[4]

(1) Technische Universität Chemnitz-Zwickau, Germany
(2) Ecole Polytechnique Fédérale de Lausanne, Switzerland
(3) Universität Mannheim, Germany
(4) Freie Universität Berlin, Germany

Uncertainty quantification (UQ) is concerned with including and characterising uncertainties in mathematical models. Major steps comprise proper description of system uncertainties, analysis and efficient quantification of uncertainties in predictions and design problems, and statistical inference on uncertain parameters starting from available measurements. Research in UQ addresses fundamental mathematical and statistical challenges, but has also wide applicability in areas such as engineering, environmental, physical and biological applications. This workshop focussed on mathematical challenges at the interface of applied mathematics, probability and statistics, numerical analysis, scientific computing and application domains. The workshop served to bring together experts from those disciplines in order to enhance their interaction, to exchange ideas and to develop new, powerful methods for UQ.

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Ernst Oliver, Nobile Fabio, Schillings Claudia, Sullivan Tim: Uncertainty Quantification. Oberwolfach Rep. 16 (2019), 695-772. doi: 10.4171/OWR/2019/12