- Schedule of Classes - May 19, 2019 7:14PM EDT
- Course Catalog - May 19, 2019 7:15PM EDT
Course information provided by the Courses of Study 2018-2019. Courses of Study 2019-2020 is scheduled to publish mid-June.
Course covering Bayesian inference for stochastic systems, parameter estimation and Bayesian networks. Includes optimal Bayesian filtering including Kalman filter, Hidden Markov model filter, sequential Monte-Carlo (particle) filters; maximum likelihood parameter estimation including the EM algorithm; social learning models and inference; Bayesian networks and their applications. The course will emphasize applications in social systems/networks, sensing and communication systems.
When Offered Spring.Outcomes
- Students will learn state of the art methods in Bayesian state estimation, parameter estimation and applications.
Or send this URL: