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autotab

Variational Autoencoders for Heterogeneous Tabular Data

v1.0 · Mar 25, 2026 · MIT + file LICENSE

Description

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.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
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r-patched-linux-x86_64 OK
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r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies keras magrittr R6 reticulate tensorflow autotab

Version History

updated 1.0 ← 0.1.3 diff Mar 25, 2026
new 0.1.3 Mar 10, 2026
updated 0.1.3 ← 0.1.2 diff Feb 8, 2026
updated 0.1.2 ← 0.1.1 diff Feb 5, 2026
new 0.1.1 Nov 23, 2025