FINN: Forest Informed Neural Networks
A hybrid dynamic forest (gap) model (FINN) that can be configured as a fully mechanistic, process-based model, like classic forest gap models, or with its demographic processes (growth, mortality, regeneration) replaced by deep neural networks (DNNs), or any combination of the two. Provides functions to define a model and its mechanistic or empirical components, calibrate it to forest inventory data, and interpret the calibrated processes. FINN is implemented with the 'torch' package, which supplies GPU support and the automatic differentiation used to calibrate the model by stochastic gradient descent; no knowledge of 'torch' is required. The hybrid modeling approach is described in Pichler and Käber (2026) <doi:10.1111/2041-210x.70347>.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | abind, cli, stats, utils, data.table, coro, Rcpp, torch, ggplot2, glue |
| LinkingTo: | Rcpp |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2026-08-09 |
| DOI: | 10.32614/CRAN.package.FINN (may not be active yet) |
| Author: | Yannek Käber 
[aut, cre],
Maximilian Pichler
[aut] |
| Maintainer: | Yannek Käber <y.kaeber at posteo.de> |
| BugReports: | https://github.com/FINNverse/FINN/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/FINNverse/FINN, https://finnverse.github.io/FINN/ |
| NeedsCompilation: | yes |
| Materials: | README, NEWS |
| CRAN checks: | FINN results |
Documentation:
Downloads:
| Package source: | FINN_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): FINN_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): FINN_0.1.0.tgz |
Linking:
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