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SUMMARY:Convergence analysis of non-stationary and deep Gaussian process r
 egression - Aretha Teckentrup (University of Edinburgh)
DTSTART:20230126T150000Z
DTEND:20230126T160000Z
UID:TALK196093@talks.cam.ac.uk
CONTACT:Matthew Colbrook
DESCRIPTION:We are interested in the task of estimating an unknown functio
 n from data\, given as a set of point evaluations. In this context\, Gauss
 ian process regression is often used as a Bayesian inference procedure\, a
 nd we are interested in the convergence as the number of data points goes 
 to infinity. Using results from scattered data approximation\, we provide 
 a convergence analysis of the method applied to a given\, unknown function
  of interest. We are particularly interested in the case of non-stationary
  covariance kernels\, and the extension of the results to deep Gaussian pr
 ocesses.\n\nThis is joint work with Conor Osborne (University of Edinburgh
 ).\n
LOCATION:Centre for Mathematical Sciences\, MR14
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