Vorlesung: Probabilistic Graphical Models


  • Dozent(en):
  • Beginn: 19.10.2016
  • Zeiten: Wed. 12:30 - 14:00, LBH / HS III.a
  • Veranstaltungsnummer: MA-INF 4315
  • Studiengang: Master
  • Aufwand: 6 CP
  • Prüfungen: Feb 22, 13:00 - 15:00, LBH / HS III.a



This course introduces probabilistic graphical models and their use in solving problems in computer vision and machine learning. Graphical models offer a probabilistic framework for modelling and making decisions in complex scenarios with limited and noisy data.  We will cover topics such as Markov and Bayesian networks, inference techniques and parameter learning.  The theory will be demonstrated in various vision applications.

No prior knowledge of statistics is required to follow the course.  Exercises will be both theory and programming (Matlab and Python) based and be completed in groups of two.


The second exam will be held on Mar. 23 from 13:00 - 15:00 in LBH III.a.  Please bring photo ID.  You may use a non-programming calculator.

Exams have been graded and will be available on BASIS by Friday Mar. 3.  If you want to look at your marked exam, you can stop by I.81 on Wednesday Mar. 8 from 16:30 - 18:00.  

The final exam will be held on Feb. 22 from 13:00 - 15:00 in LBH III.a.  Please bring photo ID.  You may use a non-programming calculator.

If you have conflicts for attending the exercises due to other classes, please email the TAs to arrange handing in assignments before the exercise session.  

First lecture starts on October 19, 2016!


Weitere Dokumente


Übung 1: ProbRefresh
Übungsblatt  (PDF-Dokument, 53 KB)
Übung 2: BayesianNetworks
Übungsblatt  (PDF-Dokument, 67 KB)
Übung 3: MarkovNetworks
Übungsblatt  (PDF-Dokument, 126 KB)
Übung 4: VarElim
Übungsblatt  (PDF-Dokument, 104 KB)
Übung 5: MsgPassing
Übungsblatt  (PDF-Dokument, 151 KB)
Übung 6: MsgPassing2
Übungsblatt  (PDF-Dokument, 92 KB)
Übung 7: JunctionSamplingI
Übungsblatt  (PDF-Dokument, 107 KB)
Übung 8: MAP
Übungsblatt  (PDF-Dokument, 336 KB)
Übung 9: Param
Übungsblatt  (PDF-Dokument, 158 KB)
Übung 10: EM
Übungsblatt  (PDF-Dokument, 138 KB)