STAT 648: GRAPH MODELS & NETWORKS
Spring 2027 · Section 001 · CRN 26503
Graphical models – aka Bayes networks, Markov networks, Gaussian networks, etc. – have been widely used to represent complex phenomena with dependence. The course aims to stimulate interest in graphical models and covers directed and undirected graphical models, exponential-family representations of graphical models, statistical inference, finite-sample and large-sample properties, and applications.
- Credits
- 3
- Instructors
- Christine Peterson