The object of this model is to minimize ℒ(𝑡) = ‖𝜖 -𝜖̂!‖ # via mini-batch gradient descent optimization. Once this model is well trained, new sample points can be generated. Any sample point 𝑥 % ∈ 𝒩(0, Ι) is iteratively denoised via eq. 7 for t = T, . . ., 0 to obtain a new data point x0.