This course covers computational approaches to probabilistic and decision-theoretic inference. A particular focus is placed on the use of graphical models, particularly Bayesian networks. Medical applications of the techniques and representations are emphasized.
Prerequisites: an understanding of basic probability and decision theory
Recitations: none
Expected class size:
Frequency: This course is offered every other year. To determine whether this course will be offered during a specific term, please check with the ISP Administrator.
Credits: 3