Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

280390 VO MA PE 01 VO Inverse Problems (NPI) (2019W)

4.00 ECTS (3.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie - Geophysik und
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Register/Deregister for this course

Details

max. 20 participants
Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 03.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 10.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 17.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 24.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 31.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 07.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 14.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 21.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 28.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 05.12. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 12.12. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 09.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 16.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 23.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 30.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II

Information

Aims, contents and method of the course

The course deals with the resolution of ill posed problems (inverse problems from physics, but also, depending on the students, simple problems from data science of data fitting type). More precisely, the following aspects will be presented:
-- Linear regression (and statistical aspects of least squares)
-- Discretization of inverse problems (mainly integrals)
-- Ill posed problems and rank deficiency
-- Tikhonov regularization
-- Nonlinear regression (Newton method,...).
-- Bayesian approach

All these chapter will be complemented with exercises (Matlab or Python).

Assessment and permitted materials

oral examination

Minimum requirements and assessment criteria

Examination topics

Reading list

R.C. Aster, B. Borchers, C.H. Thurber: Parameter Estimation and Inverse Problems, Elsevier, 2013

Association in the course directory

Last modified: Sa 02.04.2022 00:25