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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 [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 |
Reference manual: | tfprobability.pdf |
Vignettes: |
Multi-level modeling with Hamiltonian Monte Carlo Uncertainty estimates with layer_dense_variational |
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 depends: | deepregression, deeptrafo |
Reverse imports: | ML2Pvae |
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.