Topic outline

  • General

    The course is organized partially remotely. The lectures have been prerecorded and published at the Materials section of the course's MyCourses homepage. On Monday at 14.15-16.00 (the first lecture time in Sisu), there is a contact teaching questions and answers session in M3 (M234) starting on February 28. A weekly exercise session is held on Friday at 14.15-16.00 in classroom M2 (M233) beginning on March 4. 

    The 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


    There is a Zulip discussion group for the course that you can join through the link: https://ms-e1654.zulip.aalto.fi/join/d47somwzvff3vnu5e7zryyam/