Variational Autoencoders for Heterogeneous Tabular Data R package autotab version 1.1 Build and train a variational autoencoder (VAE) for mixed-type tabular data (continuous, binary, categorical). Models are implemented using 'TensorFlow' and 'Keras' via the 'reticulate' interface, enabling reproducible VAE training for heterogeneous tabular datasets. Software Depends: R (>= 4.1) Imports: keras, magrittr, R6, reticulate, tensorflow Suggests: dplyr, caret, knitr, rmarkdown, testthat (>= 3.0.0) Sarah Milligan <slm1999@bu.edu> Comprehensive R Archive Network (CRAN) Sarah Milligan [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=autotab/LICENSE) 2026-07-30 application/tgz https://CRAN.R-project.org/package=autotab doi:10.32614/CRAN.package.autotab