The latex template for scribing the lecture notes is here.

1. Jan 11, 2022. Overview: Notes.

2. Jan 13, 2022. Undirected graphical models - definitions: Typed notes, Notes and Video.

3. Jan 18, 2022. Conditional independence axioms: Typed notes, Notes and Video.

4. Jan 20, 2022. Equivalence of definitions; Gaussian distributions: Typed notes, Notes and Video.

5. Jan 25, 2022. Properties of Gaussians; Maximum likelihood estimation: Typed notes, Notes and Video.

6. Feb 1, 2022. Maximum Likelihood Estimation for Gaussian graphical models: Notes and Video.

7. Feb 3, 2022. MLE for Gaussian graphical models; Chordal graphs: Notes and Video.

8. Feb 8, 2022. Learning the graph for Gaussian graphical models; Discrete graphical models: Notes and Video.

9. Feb 10, 2022. Maximum Likelihood Estimation for Log-linear models: Notes and Video.

10. Feb 15, 2022. Learning Undirected Graphs: Notes and Video.

11. Feb 17, 2022. Learning Undirected Graphs; Introduction to causality: Notes and Video.

12. Mar 3, 2022. Directed graphical models: Notes and Video.

13. Mar 8, 2022. Markov equivalence. Directed Gaussian graphical models: Notes and Video.

14. Mar 10, 2022. Directed Gaussian graphical models: Notes and Video.

15. Mar 15, 2022. Learning directed acyclic graphs from observations: Notes and Video.

16. Mar 17, 2022. Structural equation models and interventions: Notes and Video.

17. Mar 22, 2022. Identification of causal effects from observations: Notes and Video.

18. Mar 24, 2022. Counterfactuals, Instrumental variables, and Linear Causal Models: Notes and Video.