Discretely Relaxing Continuous Variables for tractable Variational Inference

We explore a new research direction in Bayesian variational inference with discrete latent variable priors where we exploit Kronecker matrix algebra for efficient and exact computations of the evidence lower bound (ELBO). The proposed DIRECT approach has several advantages over its predecessors; (i) it can exactly compute ELBO gradients (i.e.