{ "_id": "6a1019c6acfb0bcc41c86137", "Package": "rCISSVAE", "Title": "Clustering-Informed Shared-Structure VAE for Imputation", "Version": "1.0.1", "Authors@R": "c( person(given = \"Yasin\", family = \"Khadem Charvadeh\", email = \"khademy@mskcc.org\", role = c(\"aut\")),\nperson(given = \"Kenneth\", family = \"Seier\", role = c(\"aut\")),\nperson( given = c(\"Katherine\", \"S.\"), family = \"Panageas\", role = c(\"aut\")),\nperson(given = \"Danielle\", family = \"Vaithilingam\", email = \"vaithid1@mskcc.org\", role = c(\"aut\", \"cre\")),\nperson(given = \"Mithat\", family = \"Gönen\", role = c(\"aut\")),\nperson(given = \"Yuan\", family = \"Chen\", email = \"cheny19@mskcc.org\", role = c(\"aut\"))\n)", "Maintainer": "Danielle Vaithilingam ", "Description": "Implements the Clustering-Informed Shared-Structure\nVariational Autoencoder ('CISS-VAE'), a deep learning framework\nfor missing data imputation introduced in Khadem Charvadeh et\nal. (2025) . The model accommodates all\nthree types of missing data mechanisms: Missing Completely At\nRandom (MCAR), Missing At Random (MAR), and Missing Not At\nRandom (MNAR). While it is particularly well-suited to MNAR\nscenarios, where missingness patterns carry informative\nsignals, 'CISS-VAE' also functions effectively under MAR\nassumptions.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "URL": "https://ciss-vae.github.io/rCISS-VAE/", "BugReports": "https://github.com/CISS-VAE/rCISS-VAE/issues", "Config/testthat/edition": "3", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "LazyData": "true", "Config/pak/sysreqs": "cmake make libicu-dev libpng-dev libuv1-dev\nlibxml2-dev libssl-dev perl python3 libnode-dev", "Repository": "https://ciss-vae.r-universe.dev", "Date/Publication": "2026-05-14 13:12:39 UTC", "RemoteUrl": "https://github.com/ciss-vae/rciss-vae", "RemoteRef": "HEAD", "RemoteSha": "b13cacd85446e69e417d5ab674b11bd161675845", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-14 15:30:34 UTC", "User": "root" }, "Author": "Yasin Khadem Charvadeh [aut],\nKenneth Seier [aut],\nKatherine S. 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