Syllabus

All the material that we have covered in class make up the syllabus, including the homework exercises. In terms of the course book, we have covered the following:

  • Chapter 2 - Foundations
    • All sections except 2.1.6.
  • Chapter 3 - The Bayesian Network Representation

    • All sections.

  • Chapter 4 - Undirected Graphical Models

    • All sections except 4.4.2 and 4.6.

  • Chapter 9 - Exact Inference: Variable Elimination

    • Only sections 9.2, 9.3, and 9.4.1-9.4.2.

  • Chapter 10 - Exact Inference: Clique Trees

    • All sections.

  • Chapter 17 - Parameter Estimation

    • All sections except 17.2.4, 17.5, and most of 17.6.

    • Included from 17.6: 17.6.1 and 17.6.2.2 up til Lemma 17.2.

  • Chapter 18 - Structure Learning in Bayesian Networks

    • All sections except 18.4.4, 18.5, and 18.6.

  • Chapter 20 - Learning Undirected Models

    • All except 20.3.2-20.3.4, 20.4.2, 20.5, 20.6.2, and 20.7.4-20.7.5.

  • Chapter 21 - Causality

    • All except 21.4-21.6 and 21.7.4.

Published May 10, 2023 12:06 PM - Last modified May 10, 2023 12:06 PM