Explore probabilistic programming in this 1-hour 10-minute tutorial by Kevin Smith from MIT, presented at the BMM Summer Course 2018. Dive into key concepts such as computational theory of mind, intuitive physics engine, and probabilistic inference. Learn about the structure of probabilistic languages, storing variables and attributes, and using functions. Practice with hands-on problems covering concepts like flip away, memoization, and recursion. Gain insights into how neurons contribute to probabilistic programming and understand the advantages of using web-based probabilistic programming languages.
Overview
Syllabus
Intro
Toby Gersonburg
Tug of War
Strength
Overview
What is Thinking
Computational Theory of Mind
Intuitive Physics Engine
Structure and Probability
Probabilistic Language
Probabilistic Inference
How do neurons give rise to probabilistic programming
Why are we using web ppl
Storing Variables
Storing Attributes
Redefine Attributes
Else Statement
QuestionMark Operator
Functions
Differences from JavaScript
Practice Problems
Concepts
Flip Away
Memoization
Recursion
Bonus
Questions
Taught by
MITCBMM
