sdewaele

using LinearAlgebra
import Base.exp
import LinearAlgebra.exp!

function expmchk()
# EXPMCHK Check the class of input A and
#    initialize M_VALS and THETA accordingly.
    m_vals = [3 5 7 9 13];
    # theta_m for m=1:13.
                theta = [#3.650024139523051e-008

sdewaele

using ZygoteRules:@adjoint
using Zygote
using Random

function ngradient(f, xs::AbstractArray...)
  grads = zero.(xs)
  for (x, Δ) in zip(xs, grads), i in 1:length(x)
    δ = sqrt(eps())
    tmp = x[i]
    x[i] = tmp - δ/2

sdewaele

using CUDA
using StatsBase
import StatsBase: fit, transform!, reconstruct!, mean_and_std

"""
Standardization (Z-score transformation)
"""
struct ZScoreTransformGeneric{T<:Real,U<:AbstractVector{T}} <: AbstractDataTransform
    len::Int
    dims::Int