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Professur Numerische Mathematik
Professur Numerische Mathematik
Professur Numerische Mathematik 

Mathematical Methods of Uncertainty Quantification (4V, 2Ü) Prof. Ernst, SS 2022

Topics of this Course:
  • Mathematical descriptions of uncertainty
  • Random differential equations
  • Representation of random fields
  • Monte Carlo methods
  • Stochastic collocation methods
  • Bayesian inverse problems

Announcements

Class Hours

Keine Lehrveranstaltung gefunden.

Course Materials

Supplementary Literature

UQ, Numerical methods for random differential equations:
  • Tim Sullivan: Introduction to Uncertainty Quantification, Springer 2015.
  • Gabriel J. Lord, Catherine E. Powell and Tony Shardlow: An Introduction to Computational Stochastic PDEs, Cambridge University Press, 2014.
  • Ralph C. Smith: Uncertainty Quantification: Theory, Implementation and Applications, SIAM 2014.
  • Dongbin Xiu: Numerical Methods for Stochastic Computations, Princeton University Press 2010.
  • Olivier Le Maitre und Omar M. Knio: Spectral Methods for Uncertainty Quantification, Springer 2010.
Background in Statistics and Probability Theory
  • David Williams, Weighing the Odds: A Course in Probability and Statistics, Cambridge University Press, 2001.