Computer Science 688 - Probabilistic Graphical Models

Spring
2022
01
3.00
Daniel Sheldon

TU TH 4:00PM 5:15PM

UMass Amherst
27845
Goessmann Laboratory room 20
sheldon@cs.umass.edu
This course will cover Bayesian and Markov networks and their dynamic and relational extensions; exact and approximate inference methods; estimation of both the parameters and structure of graphical models.

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.

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