To maximize our training objective, we must be able to compute To compute ∇ Θq L gen , we use a reparameterization trick.
we can rewrite z ∼ q(z | x , x) as z = h(α) where h is a deterministic function differentiable with respect to Θ q and α ∼ p(α) is an auxiliary random variable not depending on Θ q (the details of h and α are given in Appendix 6).