Computer Science 688 - Probabilistic Graphical Models

This course will cover Bayesian and Markov networks; exact and approximate inference methods; estimation of the parameters and structure of graphical models; broader topics in probabilistic inference for statistics and machine learning.

Open to graduate Computer Science students only. SEATS HELD FOR INCOMING GRAD STUDENT REGISTRATION. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.