Gaussian processes are a collection of random variables, any finite number of which have a joint Gaussian distribution. They are used to define a distribution over functions, allowing for modeling of uncertainty in predictions and function estimation, making them particularly valuable in applications such as regression and classification, where uncertainty quantification is crucial.
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