[ctb],
RStudio [cph]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: | 0.11.0.0 |
| 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 [ctb],
RStudio [cph] |
| Maintainer: | Sigrid Keydana <sigrid 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: |
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: tfprobability_0.11.0.0.zip, r-release: tfprobability_0.11.0.0.zip, r-oldrel: tfprobability_0.10.0.0.zip |
| macOS binaries: | r-release: tfprobability_0.10.0.0.tgz, r-oldrel: tfprobability_0.11.0.0.tgz |
| Old sources: | tfprobability archive |
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