Gaussian Processes

Gaussian processes are non-parametric Bayesian models that define distributions over functions rather than parameters. They excel at modeling continuous data and quantifying uncertainty.

Key characteristics include principled uncertainty estimates and automatic adaptation of complexity. Imagine predicting temperature throughout a day with confidence intervals.

They are particularly useful in regression tasks where uncertainty estimation is crucial.