Monte Carlo Methods
Mihriban Ceylan, Jacob Heieck, Andreas Neuenkirch
2+2 SWS / 6 ECTS, B.Sc.
Monte Carlo methods are algorithms which use random numbers. They have various applications, e.g. in the simulation of complex stochastic systems or in the numerical treatment of high-dimensional deterministic problems.
This course will address the following topics
- pseudo random numbers
- sampling from distributions
- Monte Carlo quadrature
- convergence of Monte Carlo estimators
- variance-cost reduction methods
- comparison of deterministic and randomized algorithms
We will also cover the seminal work of Robbins and Monro (1951) as a teaser on stochastic approximation.
Lecture and Exercise classes
- Lecture: Monday, 13:45 in C 013 Hörsaal (A 5, 6 Bauteil C). The lectures will start in the first week.
- Exercises: Please register for your exercise group via ILIAS. The classes are Monday, 15:30, A 203 (B 6, 23–25) and Tuesday, 13:45 in C 013. The exercises will start in the second week.
Lecture notes and exercises sheets will be provided via ILIAS.
Exams
The dates for the oral exams (30 min) will be announced during the course. For admission to the exam, you have to achieve 50 % of the exercise points. There will be 12 exercise sheets with two Abgabeaufgaben each, which have to be handed in. The Abgabeaufgaben will be theoretical and practical (Matlab).