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unfold: Mapping Hidden Geometry into Future Sequences

A variational mapping approach that reveals and expands future temporal dynamics from folded high-dimensional geometric distance spaces, unfold turns a set of time series into a 4D block of pairwise distances between reframed windows, learns a variational mapper that maps those distances to the next reframed window, and produces horizon-wise predictive functions for each input series. In short: it unfolds the future path of each series from a folded geometric distance representation.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: torch (≥ 0.11.0), purrr (≥ 1.0.1), imputeTS (≥ 3.3), lubridate (≥ 1.9.2), ggplot2 (≥ 3.5.1), scales (≥ 1.3.0), abind (≥ 1.4-5), coro (≥ 1.1.0)
Suggests: knitr, testthat (≥ 3.0.0)
Published: 2025-08-26
DOI: 10.32614/CRAN.package.unfold
Author: Giancarlo Vercellino [aut, cre, cph]
Maintainer: Giancarlo Vercellino <giancarlo.vercellino at gmail.com>
License: GPL-3
URL: https://rpubs.com/giancarlo_vercellino/unfold
NeedsCompilation: no
Materials: NEWS
CRAN checks: unfold results

Documentation:

Reference manual: unfold.html , unfold.pdf

Downloads:

Package source: unfold_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): unfold_1.0.0.tgz, r-oldrel (arm64): unfold_1.0.0.tgz, r-release (x86_64): unfold_1.0.0.tgz, r-oldrel (x86_64): unfold_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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