389.235 Graph Information Processing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2024S, VO, 3.0h, 4.5EC

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VO Lecture
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to remember and reproduce problems and methods in the areas of probabilistic graphical models and graph signal processing. They are able to adapt these methods to practical engineering applications by formulating and modelling the problem mathematically, devising  analytical or algorithmic solutions, and characterizing the performance and complexity of their methods qualitatively and quantitatively.

Subject of course

  • fundamentals of probability and graph theory
  • application examples
  • types of graphical models 
    • Bayesian networks
    • Markov random fields
    • factor graphs
  • methods and algorithms for inference on graphs
    • message passing, belief propagation
    • variational methods
  • Graph signal processing
    • graph shift and graph Fourier transform
    • graph filters
    • graph signal recovery
    • graph learning
    • clustering
  • Graph neural networks (GNN)

Teaching methods

Conventional lectures on the blackboard supported by digital teaching materials.

Mode of examination

Written and oral

Additional information

The lecture is held on Tuesday 13:00-14:30 and Wednesday 11:00-12:00 in seminar room 389 (room no. CG 0118).

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue13:00 - 14:3005.03.2024 - 25.06.2024Sem 389 Graph Information Processing
Wed11:00 - 12:0006.03.2024 - 26.06.2024Sem 389 Graph Information Processing
Graph Information Processing - Single appointments
DayDateTimeLocationDescription
Tue05.03.202413:00 - 14:30Sem 389 Graph Information Processing
Wed06.03.202411:00 - 12:00Sem 389 Graph Information Processing
Tue12.03.202413:00 - 14:30Sem 389 Graph Information Processing
Wed13.03.202411:00 - 12:00Sem 389 Graph Information Processing
Tue19.03.202413:00 - 14:30Sem 389 Graph Information Processing
Wed20.03.202411:00 - 12:00Sem 389 Graph Information Processing
Tue09.04.202413:00 - 14:30Sem 389 Graph Information Processing
Wed10.04.202411:00 - 12:00Sem 389 Graph Information Processing
Tue16.04.202413:00 - 14:30Sem 389 Graph Information Processing
Wed17.04.202411:00 - 12:00Sem 389 Graph Information Processing
Tue23.04.202413:00 - 14:30Sem 389 Graph Information Processing
Wed24.04.202411:00 - 12:00Sem 389 Graph Information Processing
Tue30.04.202413:00 - 14:30Sem 389 Graph Information Processing
Tue07.05.202413:00 - 14:30Sem 389 Graph Information Processing
Wed08.05.202411:00 - 12:00Sem 389 Graph Information Processing
Tue14.05.202413:00 - 14:30Sem 389 Graph Information Processing
Wed15.05.202411:00 - 12:00Sem 389 Graph Information Processing
Wed22.05.202411:00 - 12:00Sem 389 Graph Information Processing
Tue28.05.202413:00 - 14:30Sem 389 Graph Information Processing
Wed29.05.202411:00 - 12:00Sem 389 Graph Information Processing

Examination modalities

written exam: mathematical solution of simple problems; multiple choice theory questions

oral exam: comprehension questions regarding the course materials

Course registration

Not necessary

Curricula

Study CodeObligationSemesterPrecon.Info
066 507 Telecommunications Mandatory elective

Literature

Lecture notes are available in a draft version.

Previous knowledge

probability and random variables, linear algebra, signals and systems theory

Preceding courses

Accompanying courses

Language

English