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 |
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