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 (≥ 2.0.0), reticulate, keras, magrittr
Suggests: testthat (≥ 2.1.0), knitr
Published: 2019-10-30
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
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_0.8.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
OS X binaries: r-release: not available, r-oldrel: not available


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