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Sequential Monte Carlo Methods2021HT
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Course plan
About the course
The aim of this course is to provide an introduction to the theory and application of sequential Monte Carlo (SMC) methods. To this end we will start by studying the use of SMC for inference in nonlinear dynamical systems. It will be shown how SMC can be used to solve challenging parameter (system identification) and state inference problems in nonlinear dynamical systems. Importantly, we will also discuss SMC in a more general context, showing how it can be used as a generic tool for sampling from complex probability distributions.
Format
This is an intensive course given during one or two weeks in August/September
2021 (dates TBD). The course consists of lectures, exercise sessions and
hand-in assignments.
The course has previously been given at Uppsala University, see
http://www.it.uu.se/research/systems_and_control/education/2019/smc
for more information.
Starting in 2021, the intention is to run it every second year, alternating
between Linköping (2021, 2025, ...) and Uppsala (2023, 2027, ...)
Credits
6 hp
Teachers
Fredrik Lindsten (LiU/IDA)
Johan Alenlöv (LiU/IDA)
Thomas Schön (UU/IT)
Examination
Via successfully completing and handing in the hand-in assignments.
Page responsible: Director of Graduate Studies
