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401-4671-00L 9 Credits MSC D-MATH
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Advanced Numerical Methods for CSE

Lecturers & Examiners: Prof. Dr. Ralf Hiptmair
VVZ CR 4.0

Last Updated: 2026-02-05 16:14:46

Abstract

This course will focus on teaching different advanced topics in numerical methods for science and engineering. The main aim would be introduce novel algorithms and discuss their implementation.

Objective

* Understanding the mathematical foundations and design principles of a selection of modern numerical methods for challenging problems. * Ability to adapt the presented paradigms and algorithms to modified or new problems arising from applications in computational science and engineering. * Ability to judge the scope, strengths and weaknesses of the numerical methods covered in this course and of methods derived from them. * Skills in translating a high-level description of an algorithm into efficient code.

Content

I. Local low-rank compression II. Convolution quadrature III. (Algebraic) multigrid methods IV. Approximation, interpolation, and quadrature in high dimensions

Resources

Lecture Notes

Lecture material will be created during the course and will be made available.

Learning Materials (Links)

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes
During the teaching period students are expected to give a 10-15-minute oral code review and answer questions concerning selected homework programming assignments. The code review is regarded as a mandatory performance element that will contribute 20% of the final grade.

Course Components

Type Title Time & Place Hours
lecture Advanced Numerical Methods for CSE
on 15 November and 6 Decemeber 2023 in HG G 5
  • Mon 10:15-12:00 (HG G 19.1)
  • Wed 08:15-10:00 (HG G 19.1)
  • Wed 08:15-10:00 (HG G 5)
4 h weekly
exercise Advanced Numerical Methods for CSE
Groups are selected in myStudies. tentatively Thu 8-10 or Fri 14-16
  • Thu 08:15-10:00 (HG G 26.1)
  • Fri 14:15-16:00 (ML H 34.3)
2 h weekly
practical/laboratory course Advanced Numerical Methods for CSE No time listed 1 h weekly

Offered In

  • Computational Science and Engineering Master
    • Core Courses (In the ‘core courses’ subcategory, at least two course units must be successfully completed. Only one of the two course units 263-5210-00L Probabilistic Artificial Intelligence resp. 252-0535-00L Advanced Machine Learning may be recognised for credits as a core course. However, the other course unit may be recognised for a different category.)