MS&E355
Influence Diagrams and Probabilistics Networks
Management Science and Engineering
ENGR - School of Engineering
Course Description
Network representations for reasoning under uncertainty: influence diagrams, belief networks, and Markov networks. Structuring and assessment of decision problems under uncertainty. Learning from evidence. Conditional independence and requisite information. Node reductions. Belief propagation and revision. Simulation. Linear-quadratic-Gaussian decision models and Kalman filters. Dynamic processes. Bayesian meta-analysis. Limited Enrollment. Prerequisites: 220, 252, or equivalents, or consent of instructor.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Programs
MS&E355
is a
completion requirement
for: