module Inputs: sig
.. end
Derivatives of the (cross-) covariance matrix of inputs.
type
diag
Representation of precomputed data for calculating the
derivative of the diagonal of the covariance matrix of
inputs.
type
cross
Representation of precomputed data for calculating the
derivative of the cross-covariance matrix between inputs
and inducing inputs.
val calc_shared_diag : Eval.Kernel.t ->
Gpr_interfaces.Specs.Eval.Inputs.t ->
Lacaml.D.vec * diag
calc_shared_diag kernel inputs
Returns the pair (eval, diag)
,
where eval
is the diagonal of the covariance matrix of inputs
for
kernel
, and diag
is the precomputed data needed for taking
derivatives.
val calc_shared_cross : Eval.Kernel.t ->
inputs:Gpr_interfaces.Specs.Eval.Inputs.t ->
inducing:Gpr_interfaces.Specs.Eval.Inducing.t ->
Lacaml.D.mat * cross
calc_shared_cross kernel ~inputs ~inducing
Returns the pair (eval,
cross)
, where eval
is the cross-covariance matrix of inputs and
inducing inputs for kernel
, and diag
is the precomputed data
needed for taking derivatives.
val calc_deriv_diag : diag ->
Gpr_interfaces.Specs.Deriv.Hyper.t -> Gpr_interfaces.diag_deriv
calc_deriv_diag diag hyper
Returns the derivative of the
diagonal of the covariance matrix of inputs given precomputed data
diag
and the hyper
-variable.
val calc_deriv_cross : cross ->
Gpr_interfaces.Specs.Deriv.Hyper.t -> Gpr_interfaces.mat_deriv
calc_deriv_cross cross hyper
Returns the derivative of the
cross-covariance matrix of the inputs and inducing inputs given
precomputed data cross
and the hyper
-variable.