Vorlesung: Probabilistic Graphical Models


  • Dozent(en):
  • Beginn: 18.10.2017
  • Zeiten: Wed. 12:15 - 13:45, LBH / HS III.a
  • Veranstaltungsnummer: MA-INF 4315
  • Studiengang: Master
  • Aufwand: 6 CP



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.


First lecture starts on October 18, 2017. See you there!

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