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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "soilVAE" in publications use:'
type: software
license: MIT
title: 'soilVAE: Supervised Variational Autoencoder Regression via ''reticulate'''
version: 0.1.9
doi: 10.5281/zenodo.18715456
identifiers:
- type: doi
  value: 10.32614/CRAN.package.soilVAE
- type: url
  value: https://github.com/HugoMachadoRodrigues/soilVAE/
abstract: Supervised latent-variable regression for high-dimensional predictors such
  as soil reflectance spectra. The model uses an encoder-decoder neural network with
  a stochastic Gaussian latent representation regularized by a Kullback-Leibler term,
  and a supervised prediction head trained jointly with the reconstruction objective.
  The implementation interfaces R with a 'Python' deep-learning backend and provides
  utilities for training, tuning, and prediction.
authors:
- family-names: Rodrigues
  given-names: Hugo
  email: rodrigues.machado.hugo@gmail.com
preferred-citation:
  type: manual
  title: 'soilVAE: Supervised Variational Autoencoder Regression for Soil Spectroscopy'
  authors:
  - family-names: Rodrigues
    given-names: Hugo
    email: rodrigues.machado.hugo@gmail.com
  year: '2026'
  notes: R package version 0.1.2
  url: https://CRAN.R-project.org/package=soilVAE
  doi: 10.5281/zenodo.18715456
repository: https://hugomachadorodrigues.r-universe.dev
repository-code: https://github.com/HugoMachadoRodrigues/soilVAE
commit: a9b8f4dc224e59e931b3f092d5487d8b7fae6e44
url: https://hugomachadorodrigues.github.io/soilVAE/
date-released: '2026-03-12'
contact:
- family-names: Rodrigues
  given-names: Hugo
  email: rodrigues.machado.hugo@gmail.com