Inverse Problems, Krylov Methods, and Dog Pictures


Solving inverse problems in imaging can be very challenging due to the inherent ill-posedness and high dimensionality. To deal with this, one often employs efficient regularisation methods that enforce some additional known properties of the solution. In this talk, we shall consider Krylov subspace-based regularization approaches that combine direct matrix factorization methods on small subproblems with iterative solvers.

Feb 18, 2021 10:15 AM
Bath Postgraduate Student Seminar

By the end of this PSS talk you should:

  • Understand how inverse problems may arise and why they can be finicky to deal with
  • Feel happy with the idea of Tikhonov regularisation
  • Get the gist of how iterative Krylov methods, such as LSQR and FLSQR, work
  • Be able to name my dogs