<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>sarahmilligan-hub.r-universe.dev</title><link>https://sarahmilligan-hub.r-universe.dev</link><description>Recent package updates in sarahmilligan-hub</description><generator>R-universe</generator><image><url>https://github.com/sarahmilligan-hub.png</url><title>R packages by sarahmilligan-hub</title><link>https://sarahmilligan-hub.r-universe.dev</link></image><lastBuildDate>Thu, 21 May 2026 21:04:15 GMT</lastBuildDate><item><title>[sarahmilligan-hub] autotab 1.0.1</title><author>slm1999@bu.edu (Sarah Milligan)</author><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.</description><link>https://github.com/r-universe/sarahmilligan-hub/actions/runs/26253839536</link><pubDate>Thu, 21 May 2026 21:04:15 GMT</pubDate><r:package>autotab</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://sarahmilligan-hub.r-universe.dev</r:repository><r:upstream>https://github.com/sarahmilligan-hub/autotab</r:upstream></item></channel></rss>