Joint Distributions for TensorFlow Probability

Dan Piponi; Dave Moore; Joshua V. Dillon

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Joint Distributions for TensorFlow Probability

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arxiv 2001.11819 v1 pith:2KAIXRKT submitted 2020-01-22 cs.PL cs.LGstat.COstat.ML

Dan Piponi , Dave Moore , Joshua V. Dillon This is my paper · ORCID

classification cs.PLcs.LGstat.COstat.ML

keywords probabilitytensorflowalgorithmscanonicalcentraldeclarativedescribedirected

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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.

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