tfprobability: Interface to 'TensorFlow Probability'

Interface to 'TensorFlow Probability', a 'Python' library built on 'TensorFlow' that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', 'GPU'). 'TensorFlow Probability' includes a wide selection of probability distributions and bijectors, probabilistic layers, variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.

Version:	0.15.2
Imports:	tensorflow (≥ 2.4.0), reticulate, keras, magrittr
Suggests:	tfdatasets, testthat (≥ 2.1.0), knitr, rmarkdown
Published:	2025-08-21
DOI:	10.32614/CRAN.package.tfprobability
Author:	Tomasz Kalinowski [ctb, cre], Sigrid Keydana [aut], Daniel Falbel [ctb], Kevin Kuo [ctb], RStudio [cph]
Maintainer:	Tomasz Kalinowski <tomasz.kalinowski at rstudio.com>
BugReports:	https://github.com/rstudio/tfprobability/issues
License:	Apache License (≥ 2.0)
URL:	https://github.com/rstudio/tfprobability
NeedsCompilation:	no
SystemRequirements:	TensorFlow Probability (https://www.tensorflow.org/probability)
Materials:	README, NEWS
CRAN checks:	tfprobability results

Documentation:

Reference manual:	tfprobability.html , tfprobability.pdf
Vignettes:	Multi-level modeling with Hamiltonian Monte Carlo (source, R code) Uncertainty estimates with layer_dense_variational (source, R code)

Downloads:

Package source:	tfprobability_0.15.2.tar.gz
Windows binaries:	r-devel: tfprobability_0.15.2.zip, r-release: tfprobability_0.15.2.zip, r-oldrel: tfprobability_0.15.2.zip
macOS binaries:	r-release (arm64): tfprobability_0.15.2.tgz, r-oldrel (arm64): tfprobability_0.15.2.tgz, r-release (x86_64): tfprobability_0.15.2.tgz, r-oldrel (x86_64): tfprobability_0.15.2.tgz
Old sources:	tfprobability archive

Reverse dependencies:

Reverse imports:

deepspat, ML2Pvae

Linking:

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