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Bayesian Networks are a powerful probabilistic graphical model used for reasoning under uncertainty. They are based on the principles of Bayesian probability theory and provide a compact representation of complex probabilistic relationships among variables. Bayesian Networks have been successfully applied to a wide range of tasks, including diagnostics, decision support systems, and natural language processing. They are particularly useful in situations where there is limited or noisy data, as they can still provide reliable estimates of the probabilities of different outcomes.