19223901
Vorlesung
Uncertainty Quantification and quasi-Monte Carlo
Claudia Schillings
Literaturhinweise
The following books will be relevant:
- O. P. Le Maître and O. M. Knio. Spectral Methods for Uncertainty Quantification: With Applications to Computational Fluid Dynamics. Scientific Computation. Springer, New York, 2010.
- R. C. Smith. Uncertainty Quantification: Theory, Implementation, and Applications, volume 12 of Computational Science & Engineering. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2014.
- T. J. Sullivan. Introduction to Uncertainty Quantification. Springer, New York, in press.
- D. Xiu. Numerical Methods for Stochastic Computations: A Spectral Method Approach. Princeton University Press, Princeton, NJ, 2010.
16 Termine
Regelmäßige Termine der Lehrveranstaltung
Mo, 17.10.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 24.10.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 31.10.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 07.11.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 14.11.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 21.11.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 28.11.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 05.12.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 12.12.2022 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 02.01.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 09.01.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 16.01.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 23.01.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 30.01.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 06.02.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo
Mo, 13.02.2023 12:00 - 14:00
Uncertainty Quantification and quasi-Monte Carlo