Joint Distributions for TensorFlow Probability
Dan P. Piponi, Dave Moore, Joshua V. Dillon · arXiv (Cornell University) · 2020
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.