Bayesian Learning
Programme Leader: Kerrie Mengersen
Deputy Leader: Richard Gerlach
Programme Goals
The Bayesian Learning programme comprises researchers from both Engineering and Statistics backgrounds, reflecting the strong interdisciplinary nature of the Centre. Five main areas of research are identified in the programme: system identification, Markov Chain Monte Carlo (MCMC) methods, Bayesian modelling, nonlinear and mixture modelling, and robot location and vision.
Projects
C.1 Markov Chain Monte Carlo (MCMC) Project
C.2 Bayesian Modelling
C.3 Control Oriented System Estimation
C.4 Nonlinear and Mixture Modelling
C.5 Robot Location and Vision