Computer Science 688 - Probabilistic Graphical Models

Spring
2026
01
3.00
Benjamin Marlin

M W 4:00PM 5:15PM

UMass Amherst
85173
Goessmann Lab Addtn rm 151
marlin@cs.umass.edu
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/academics/course-overrides.

Permission is required for interchange registration during the add/drop period only.
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