Derivatives of the (cross-) covariance matrix of inputs.
Representation of precomputed data for calculating the derivative of the diagonal of the covariance matrix of inputs.
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 -> Eval.Inputs.t -> Lacaml.D.vec * diagcalc_shared_diag kernel inputs
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:Eval.Inputs.t ->
inducing:Eval.Inducing.t ->
Lacaml.D.mat * crosscalc_shared_cross kernel ~inputs ~inducing
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 -> Hyper.t -> Gpr_interfaces.diag_derivcalc_deriv_diag diag hyper
the derivative of the diagonal of the covariance matrix of inputs given precomputed data diag and the hyper-variable.
val calc_deriv_cross : cross -> Hyper.t -> Gpr_interfaces.mat_derivcalc_deriv_cross cross hyper
the derivative of the cross-covariance matrix of the inputs and inducing inputs given precomputed data cross and the hyper-variable.