Joint Distributions for TensorFlow Probability

Dan Piponi, Dave Moore, Joshua V. Dillon

Abstract: A central tenet of probabilistic programming is that a model is specified exactly once in a canonical representation which is usable by inference algorithms. We describe JointDistributions, a family of declarative representations of directed graphical models in TensorFlow Probability.