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Joint Distributions for TensorFlow Probability
January 22, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Dan Piponi, Dave Moore, Joshua V. Dillon
arXiv ID
2001.11819
Category
cs.PL: Programming Languages
Cross-listed
cs.LG,
stat.CO,
stat.ML
Citations
17
Venue
arXiv.org
Last Checked
3 months ago
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.
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