Reviews: Discretely Relaxing Continuous Variables for tractable Variational Inference

Update: read the author feedback and all reviews and still agree the paper should be accepted. This paper addresses the problem of performing Bayesian inference on mobile hardware (e.g., self-driving car, phone) efficiently. As one would imagine, approaches that operate with discrete values have an advantage in hardware. Variational inference, a method for approximate Bayesian inference, often involves continuous latent variables and continuous variational parameters. This paper's contribution is to cast everything in the discrete space with an approximating discrete prior.