The schedule is subject to change.
Date | Lecture Topics | Readings | Due Dates |
---|---|---|---|
May 7 | course overview; introduction to PPLs |
Slides
An Introduction to Probabilistic Programming (§1) Probabilistic Models of Cognition (§1–6) |
|
May 14 | semantics of probabilistic languages |
Notes
Foundations of Probabilistic Programming (§1) |
|
May 21 | Make-up day for Victoria Day |
|
|
May 28 | more semantics |
Notes
Foundations of Probabilistic Programming (§2) A Lambda-Calculus Foundation for Universal Probabilistic Programming |
|
June 4 | exact inference | Notes |
|
June 11 | exact inference |
Notes
Exact Bayesian Inference on Discrete Models via Probability Generating Functions Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions |
|
June 18 | exact inference | Notes |
project proposal due
|
June 25 | Instructor away |
|
|
July 2 | approximate inference |
Notes
An Introduction to Probabilistic Programming (§4, §5, §6) |
|
July 9 | approximate inference | Notes |
|
July 16 | automatic differentiation |
Notes
Provably Correct, Asymptotically Efficient, Higher-Order Reverse-Mode Automatic Differentiation |
|
July 23 | hacking session |
|
|
July 30 | paper presentation |
project code & report due
peer reviews due |