Joint Distributions for TensorFlow Probability
2020-01-22Code Available0· sign in to hype
Dan Piponi, Dave Moore, Joshua V. Dillon
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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.