PHY 28B
Natural Computation and Self-Organization:
The Physics of Information Processing in Complex Systems

Jim Crutchfield
chaos@ucdavis.edu; http://csc.ucdavis.edu/~chaos

Spring
WWW: http://csc.ucdavis.edu/~chaos/courses/ncaso/

Lecture 33: Bayesian Inference for Known Model Structures
Chris Strelioff, Physics, UC Davis

Reading: CMR articles IMC and OIMNC.

Topics:

  1. Goals of statistical inference
  2. Introduction to Bayesian inference
  3. Example 1: Biased Coin
  4. Unifilar HMMs and ϵ-machines
  5. Example 2: Even-Odd Process
  6. Infer transition probabilities and start state