support ScalMat in FiniteGP observation covariance

Author: st--

src/LaplaceApproximationModule.jl

@@ -179,16 +179,16 @@ function _check_laplace_inputs(
 end
 
 struct LaplaceCache{
-    Tm<:AbstractMatrix,Tv<:AbstractVector,Td<:Diagonal,Tf<:Real,Tc<:Cholesky
+    Tm<:AbstractMatrix,Tv1<:AbstractVector,Tv2<:AbstractVector,Tv3<:AbstractVector,Td<:Diagonal,Tf<:Real,Tc<:Cholesky
 }
     K::Tm  # kernel matrix
-    f::Tv  # mode of posterior p(f | y)
+    f::Tv1  # mode of posterior p(f | y)
     W::Td  # diagonal matrix of ∂²/∂fᵢ² loglik
     Wsqrt::Td  # sqrt(W)
     loglik::Tf  # ∑ᵢlog p(yᵢ|fᵢ)
-    d_loglik::Tv  # ∂/∂fᵢloglik
+    d_loglik::Tv2  # ∂/∂fᵢloglik
     B_ch::Tc  # cholesky(I + Wsqrt * K * Wsqrt)
-    a::Tv  # K⁻¹ f
+    a::Tv3  # K⁻¹ f
 end
 
 function _laplace_train_intermediates(dist_y_given_f, ys, K, f)

src/SparseVariationalApproximationModule.jl

@@ -9,7 +9,7 @@ using LinearAlgebra
 using Statistics
 using StatsBase
 using FillArrays: Fill
-using PDMats: chol_lower
+using PDMats: chol_lower, ScalMat
 
 using AbstractGPs: AbstractGPs
 using AbstractGPs:
@@ -306,7 +306,7 @@ Statistics. PMLR, 2015.
 """
 function AbstractGPs.elbo(
     sva::SparseVariationalApproximation,
-    fx::FiniteGP{<:AbstractGP,<:AbstractVector,<:Diagonal{<:Real,<:Fill}},
+    fx::FiniteGP{<:AbstractGP,<:AbstractVector,<:Union{Diagonal{<:Real,<:Fill},ScalMat}},
     y::AbstractVector{<:Real};
     num_data=length(y),
     quadrature=DefaultExpectationMethod(),