### Some articles on *unobserved variables, variables*:

Bayesian Network - Inference and Learning - Parameter Learning

... probability) is often complex when there are

... probability) is often complex when there are

**unobserved variables**... expectation-maximization algorithm which alternates computing expected values of the**unobserved variables**conditional on observed data, with maximizing the complete likelihood (or posterior) assuming that previously ... A more fully Bayesian approach to parameters is to treat parameters as additional**unobserved variables**and to compute a full posterior distribution over all nodes conditional upon observed data, then to integrate ...Variational Bayesian Methods

... models consisting of observed

... 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 ... inference, the parameters and latent**variables**are grouped together as "**unobserved variables**" ... an analytical approximation to the posterior probability of the**unobserved variables**, in order to do statistical inference over these**variables**...### Famous quotes containing the word variables:

“Science is feasible when the *variables* are few and can be enumerated; when their combinations are distinct and clear. We are tending toward the condition of science and aspiring to do it. The artist works out his own formulas; the interest of science lies in the art of making science.”

—Paul Valéry (1871–1945)

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