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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