A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation

23 May 2016 Thang D. Bui Josiah Yan Richard E. Turner

Gaussian processes (GPs) are flexible distributions over functions that enable high-level assumptions about unknown functions to be encoded in a parsimonious, flexible and general way. Although elegant, the application of GPs is limited by computational and analytical intractabilities that arise when data are sufficiently numerous or when employing non-Gaussian models... (read more)

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