All the material that we have covered in class make up the topics for the exam, including the homework exercises. In terms of the course book, we have covered the following:
- Chapter 2 - Foundations
- All sections except 2.1.6.
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Chapter 3 - The Bayesian Network Representation
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All sections.
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Chapter 4 - Undirected Graphical Models
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All sections except 4.4.2 and 4.6.
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Chapter 9 - Exact Inference: Variable Elimination
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Only sections 9.2, 9.3, and 9.4.1-9.4.2.
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Chapter 10 - Exact Inference: Clique Trees
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All sections.
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Chapter 17 - Parameter Estimation
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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).
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Chapter 18 - Structure Learning in Bayesian Networks
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All sections except 18.4.4, 18.5, and 18.6.
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Chapter 20 - Learning Undirected Models
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All sections except 20.3.2-20.3.4, 20.4.2, 20.5, 20.6.2, and 20.7.4-20.7.5.
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Chapter 21 - Causality
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All sections except 21.4-21.6 and 21.7.4.
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