101.795 AKNUM Numerical Methods in Uncertainty Quantification

2024S, VO, 2.0h, 3.0EC, to be held in blocked form

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VO Lecture
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to identify problems with high-dimensional structure. They are equipped to estimate approximation errors as well as the cost of  algorithms suitable for those problems.

Subject of course

Neural Networks for PDEs,  Monte Carlo related methods, numerics of stochastic PDEs and PDEs with random coefficients,

Teaching methods

Blackboard lecture supported by slides.  

Mode of examination

Oral

Additional information

Vorlesung jeden Donnerstag 14:00-16:00 Uhr (10 Minuten Pause) im Seminarraum 4. Stock grün

Erste Vorlesung am 11.4.2024

Skriptum: https://michaelfeischl.github.io/lecturenotes/highdim.pdf

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu14:00 - 16:0014.03.2024 - 27.06.2024Sem.R. DA grün 04 Vorlesung
AKNUM Numerical Methods in Uncertainty Quantification - Single appointments
DayDateTimeLocationDescription
Thu14.03.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu21.03.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu11.04.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu18.04.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu25.04.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu02.05.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu16.05.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu23.05.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu06.06.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu13.06.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu20.06.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Thu27.06.202414:00 - 16:00Sem.R. DA grün 04 Vorlesung
Course is held blocked

Examination modalities

Oral exam covering the course material

Course registration

Not necessary

Curricula

Study CodeObligationSemesterPrecon.Info
No records found.

Literature

No lecture notes are available.

Previous knowledge

basic course in numerical analysis (knowledge of FEM helps but is not necessary)

Language

if required in English