Jonas Wallin

We introduce a method to enable Hamiltonian Monte Carlo (HMC) to simulate from mixed continuous and discrete posterior distributions. In particular, we show how the "Gumbel Max Trick" and the Concrete (Gumbel-softmax) distribution can be used for constructing a continuous approximation of a categorical distribution, and how this distribution can be efficiently implemented for HMC. We also illustrate how the Concrete distribution can be incorporated into a latent discrete parameter model, resulting in the Concrete Mixture model.