The preferable way to register is via WebOodi. Alternatively you can just show up at the first lecture at 14-16 on Monday, February 24 in M3 (M234). The first exercise session is held at 14-16 on Friday, February 28 in M2 (M233).
students are assumed to participate actively in the course by weekly
returning their solutions to one home assignment (typically involving MATLAB computations). 25% of the overall grade is
based on the home assignments and 75% on a home exam.
The preliminary weekly timetable is as follows:
- Week 1: Motivation and (truncated) singular value decomposition
- Week 2: Morozov discrepancy principle and Tikhonov regularization
- Week 3: Regularization by truncated iterative methods
- Week 4: Motivation and preliminaries of Bayesian inversion, preliminaries of sampling
- Week 5: Prior models, Gaussian densities, MCMC (Metropolis-Hastings algorithm)
- Week 6: MCMC (Gibbs sampler), hypermodels