LS00EK97 Statistical Inverse Problems (5 cr)
Cooperation network course
Network: Finnish Applied Mathematics Network
Available for: Doctoral studies, Master's students, Bachelor's students and Bachelor's and Master's students
This course is offered through the Network for Applied Mathematics. These studies are available for bachelor's, master's and doctoral degree students studying at the University of Jyväskylä in the Following Educational fields:
- Natural Sciences
- Information and Communication Technologies (ICTs)
- Engineering, manufacturing and construction
Network: Education network on Inverse Problems
This course is offered through the Network for Inverse Problems. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master’s Degree Programme in Mathematics
- Master's degree Programme in Mathematics (Subject Teacher)
- Doctoral Degree Programme in Mathematics and Statistics
Description
- Bayesian interpretation of inverse problems. - Prior- and likelihood models - Posterior density models. - Inference over probability densities. - Markov chain Monte Carlo (MCMC) -algorithms. - Non-stationary inverse problems and Kalman-filters. Modelling and approximation errors.
Learning outcomes
Students will learn the basics of Bayesian inverse problems and they will learn how to apply the theory and computational methods to computational inverse problems in practice. The course develops the following generic skills: digitalization, management and development, internationality, sustainability and responsibility, critical thinking, identification and development of one's own expertise, and interaction and communication.
Additional information
Time: The course will be held only every second academic year. You can see the course implementations in Study guide, under "Course Units" or "Show past courses". This course is intended for the following student groups: - Undergraduate students in Technical Physics (MSc) - Undergraduate students in Applied Physics (MSc) - Graduate students in technology, physics and mathematics.
Description of prerequisites
Recommendations for the prior learning: Inverse Problems, Matlab programming