wolffd@0: wolffd@0:
wolffd@0:wolffd@0: g = gpgrad(net, x, t) wolffd@0:wolffd@0: wolffd@0: wolffd@0:
g = gpgrad(net, x, t)
takes a Gaussian Process data structure net
together
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of input vectors and a matrix t
of target
wolffd@0: vectors, and evaluates the error gradient g
. Each row
wolffd@0: of x
corresponds to one input vector and each row of t
wolffd@0: corresponds to one target vector.
wolffd@0:
wolffd@0: gp
, gpcovar
, gpfwd
, gperr
Copyright (c) Ian T Nabney (1996-9) wolffd@0: wolffd@0: wolffd@0: wolffd@0: