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Probabilistic Graphical Models

 

  • Organized by: Prof. Joschka Boedecker, Hao Zhu
  • Course number: 11E13MO-1228
  • Language: English
  • Location: Building 101, SR 01-016/18
  • Dates:
    • Tuesday 16:15-17:45, lectures
    • Wednesday 12:15-13:45, exercises and occasionally lectures
  • Lecture recordings, slides, exercises and solutions will be posted on ILIAS.

 

Overview:

The lecture deals with methods of Probabilistic Graphical Models that constitute an important class of machine learning algorithms. A brief content about the topics of the course can be found below.

  1. Bayesian classifiers
  2. Markov models
  3. Bayesian networks
  4. Inference with Monte Carlo methods
  5. Decision graphs
  6. Markov decision processes
  7. Graphical causal models
  8. Deep learning and graphical models

 

Format: 

The course will be given in person, lectures will be recorded and uploaded to ILIAS.

 

Exam: 

  • Format: open-book, written exam
  • Date: Sep. 9th, 10:00 -- 11:30
  • Room: Building 82, HS 00 006