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.

Imports: tensorflow (≥ 2.2.0), reticulate, keras, magrittr
Suggests: tfdatasets, testthat (≥ 2.1.0), knitr, markdown
Published: 2020-08-05
Author: Sigrid Keydana [aut, cre], Daniel Falbel [ctb], Kevin Kuo ORCID iD [ctb], RStudio [cph]
Maintainer: Sigrid Keydana <sigrid at>
License: Apache License (≥ 2.0)
NeedsCompilation: no
SystemRequirements: TensorFlow Probability (
Materials: README NEWS
CRAN checks: tfprobability results


Reference manual: tfprobability.pdf
Vignettes: Dynamic linear models
Multi-level modeling with Hamiltonian Monte Carlo
Uncertainty estimates with layer_dense_variational
Package source: tfprobability_0.11.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: tfprobability_0.11.0.0.tgz, r-oldrel: tfprobability_0.11.0.0.tgz
Old sources: tfprobability archive

Reverse dependencies:

Reverse depends: netReg
Reverse imports: ML2Pvae


Please use the canonical form to link to this page.