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soilVAE  

Supervised Variational Autoencoder Regression via 'reticulate'
View on CRAN: Click here


Download and install soilVAE package within the R console
Install from CRAN:
install.packages("soilVAE")

Install from Github:
library("remotes")
install_github("cran/soilVAE")

Install by package version:
library("remotes")
install_version("soilVAE", "0.1.10")



Attach the package and use:
library("soilVAE")
Maintained by
Hugo Rodrigues
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-17
Latest Update: 2026-03-17
Description:
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.
How to cite:
Hugo Rodrigues (2026). soilVAE: Supervised Variational Autoencoder Regression via 'reticulate'. R package version 0.1.10, https://cran.r-project.org/web/packages/soilVAE. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-08-22 19:50), 0.1.9 (2026-03-17 20:10)
Other packages that cited soilVAE R package
View soilVAE citation profile
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Complete documentation for soilVAE
Functions, R codes and Examples using the soilVAE R package
Full soilVAE package functions and examples
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