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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: 0.15.1
Imports: tensorflow (≥ 2.4.0), reticulate, keras, magrittr
Suggests: tfdatasets, testthat (≥ 2.1.0), knitr, rmarkdown
Published: 2022-09-01
DOI: 10.32614/CRAN.package.tfprobability
Author: Tomasz Kalinowski [ctb, cre], Sigrid Keydana [aut], Daniel Falbel [ctb], Kevin Kuo ORCID iD [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.pdf
Vignettes: Multi-level modeling with Hamiltonian Monte Carlo
Uncertainty estimates with layer_dense_variational

Downloads:

Package source: tfprobability_0.15.1.tar.gz
Windows binaries: r-devel: tfprobability_0.15.1.zip, r-release: tfprobability_0.15.1.zip, r-oldrel: tfprobability_0.15.1.zip
macOS binaries: r-release (arm64): tfprobability_0.15.1.tgz, r-oldrel (arm64): tfprobability_0.15.1.tgz, r-release (x86_64): tfprobability_0.15.1.tgz, r-oldrel (x86_64): tfprobability_0.15.1.tgz
Old sources: tfprobability archive

Reverse dependencies:

Reverse depends: deepregression, deeptrafo
Reverse imports: ML2Pvae

Linking:

Please use the canonical form https://CRAN.R-project.org/package=tfprobability to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.