Explores learning latent models in graphical structures, focusing on scenarios with incomplete samples and introducing the notion of distance among variables.
Introduces Bayesian estimation, covering classical versus Bayesian inference, conjugate priors, MCMC methods, and practical examples like temperature estimation and choice modeling.
