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Stochastic Methods

Description

Many of the real-life applications (e.g., in banking/insurance, mechanics, medicine, etc.) can be only approached, modelled and computed as stochastic (or random) processes. The aim of this course is to introduce the most essential mathematical concepts and computational methods from the area of stochastic and random processes and algorithms. The recurrent theme of the course is in establishing a joint stochastic/statistic perspective based on optimisation paradigm - for various computational methods and algorithms from computational science, machine learning and informatics.

 

REFERENCES

  • Handbook of Stochastic Methods: for Physics, Chemistry and the Natural Sciences; C. Gardiner, 2004;

People

 

Horenko I.

Course director

Additional information

Semester
Spring
Academic year
2019-2020
ECTS
6
Language
English
Education
Master of Science in Artificial Intelligence, Core course, Lecture, 1st year

Master of Science in Computational Science, Core course, Lecture, 1st year