A DisARM Derivation

To finish the derivation of Eq. 6, we need to compute E Tucker et al. 2017) and thus automatically choose the coupling which is favorable for the function Input images to the networks were centered with the global mean of the training dataset. The variance is measured based on 5000 Monte-Carlo samples at each iteration. In Appendix Figure 5, we compare gradient estimators for the toy problem Section 5.1, for which the REINFORCE LOO and ARM, especially as the problem becomes harder with increasing φ . We report the ELBO on training set (left column), the 100-sample bound on test set (middle column) and the variance of gradients (right column) for linear (top row) and nonlinear (bottom row) models. We report the ELBO on the training set (left), the 100-sample bound on the test set (middle), and the variance of the gradient estimator (right).