Laajuus: 5
Aikataulu: 25.02.2019 - 05.04.2019
Opetusperiodi (voimassa 01.08.2018-31.07.2020):
IV Spring (2018-2019, 2019-2020)
Osaamistavoitteet (voimassa 01.08.2018-31.07.2020):
You will learn to identify an ill-posed inverse problem and to understand the restrictions its nature imposes on the solution process. You will familiarize yourself with several classical regularization methods for finding approximate solutions to linear ill-posed problems. You will learn to formulate an inverse problem as a Bayesian problem of statistical inference and to interpret the information contained in the resulting posterior probability distribution. You will learn to numerically implement the introduced solution techniques.
Sisältö (voimassa 01.08.2018-31.07.2020):
The course’s topic is computational methods for solving inverse problems arising from practical applications. The course consists of two parts: the first three weeks focus on classic regularization techniques, the latter three weeks discuss statistical methods.
Toteutus, työmuodot ja arvosteluperusteet (voimassa 01.08.2018-31.07.2020):
Teaching methods: lectures, exercises and home exam.
Assessment methods: exercises, a home exam.
Työmäärä toteutustavoittain (voimassa 01.08.2018-31.07.2020):
Contact hours 36h (no compulsory attendance)
Self-study ca 100h
Oppimateriaali (voimassa 01.08.2018-31.07.2020):
All essential material is included in the lecture notes that are available at the course's homepage.
Korvaavuudet (voimassa 01.08.2018-31.07.2020):
Mat-1.3626
Kurssin kotisivu (voimassa 01.08.2018-31.07.2020):
https://mycourses.aalto.fi/course/search.php?search=MS-E1654
Esitiedot (voimassa 01.08.2018-31.07.2020):
MS-A00XX, MS-A01XX, MS-A02XX, MS-A050X. The courses MS-A030X, MS-C134X, MS-C1650, MS-E1460, MS-E1651, MS-E1652, MS-E2112 may also be useful.
Arvosteluasteikko (voimassa 01.08.2018-31.07.2020):
0-5
- Opettaja: Candiani Valentina
- Opettaja: Hyvönen Nuutti