| 1 | Introduction, Overview, Preliminaries | Problem Set 1 Out |
| 2 | Directed Graphical Models | |
| 3 | Undirected Graphical Models | |
| 4 | Factor Graphs; Generating And Converting Graphs | Problem Set 2 Out, Problem Set 1 Due |
| 5 | Minimal I-Maps, Chordal Graphs, Trees And Markov Chains | |
| 6 | Gaussian Graphical Models | Problem Set 3 Out, Problem Set 2 Due |
| 7 | Inference On Graphs: Elimination Algorithm | |
| 8 | Inference On Trees: Sum-Product Algorithm | Problem Set 4 Out, Problem Set 3 Due |
| 9 | Forward-Backward Algorithm, Sum-Product On Factor Graphs | |
| 10 | Sum-Product On Factor Graphs, MAP Elimination | |
| 11 | The Max-Product Algorithm | Problem Set 5 Out, Problem Set 4 Due |
| 12 | Midterm Evening Quiz (Through Lecture 11 And Problem Set 4) | |
| 13 | Gaussian Belief Propagation | |
| 14 | Gaussian HMMs And Kalman Filtering | |
| 15 | The Junction Tree Algorithm | Problem Set 6 Out, Problem Set 5 Due |
| 16 | Loopy Belief Propagation - Part I | |
| 17 | Loopy Belief Propagation - Part II | |
| 18 | Variational Inference | Problem Set 7 Out |
| 19 | MCMC Methods And Approximate MAP | Problem Set 6 Due |
| 20 | Approximate Inference By Particle Methods | Problem Set 8 Out, Problem Set 7 Due |
| 21 | Parameter Estimation In Directed Graphical Model | |
| 22 | Parameter Estimation In Undirected Graphical Model | Problem Set 9 Out, Problem Set 8 Due |
| 23 | Estimating Structure Of Directed Graphical Model | |
| 24 | Estimating Structure Of Undirected Graphical Model / Exponential Family | Problem Set 10 Out, Problem Set 9 Due |
| 25 | Parameter Estimation From Partial Observations: EM Algorithm | |
| 26 | Final Evening Quiz (Through Lecture 23 And Problem Set 9) | |
