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Variational Bayesian methods are a family of techniques for approximating intractable integrals arising in Bayesian inference and machine learning. They are typically used in complex statistical models consisting of observed variables (usually termed "data") as well as unknown parameters and latent variables, with various sorts of relationships among the three types of random variables, as might be described by a graphical model. As is typical in Bayesian inference, the parameters and latent variables are grouped together as "unobserved variables". Variational Bayesian methods are primarily used for two purposes:

To provide an analytical approximation to the posterior probability of the unobserved variables, in order to do statistical inference over these variables. To derive a lower bound for the marginal likelihood (sometimes called the "evidence") of the observed data (i.e. the marginal probability of the data given the model, with marginalization

Tourism Destination
 * Muara Kuin Floating Market, Shopping Sensation above the river.
 * Selarong Cave, Pangeran Diponegoro's Struggle Base.
 * Mount Panderman, Malang Regency, East Java.
 * Baning Tourism Forest, West Kalimantan.
 * Ban forest of Kampung Kuta, Ciamis Regency.
 * Sangeh Forest, Bali: Home to Hundreds of Wild Monkeys.
 * Jimbaran, South Kuta, Bali Province.
 * Jolosutro Beach, Blitar Regency.
 * Mount Semeru: The Highest Mountain in Java.
 * Garuda Wisnu Kencana Cultural Park.