Implements a probabilistic ensemble time-series forecaster that combines an auto-encoder with a neural decision forest whose split variables are learned through a differentiable feature-mask layer. Functions are written with 'torch' tensors and provide CRPS (Continuous Ranked Probability Scores) training plus mixture-distribution post-processing.

Fits temperature response models to rate measurements taken at different temperatures. Etienne Low-Decarie,Tobias G. Boatman, Noah Bennett,Will Passfield,Antonio Gavalas-Olea,Philipp Siegel, Richard J. Geider (2017) <doi:10.1002/ece3.3576> .

Implements the template ICA (independent components analysis) model
    proposed in Mejia et al. (2020) <doi:10.1080/01621459.2019.1679638> and the 
    spatial template ICA model proposed in proposed in Mejia et al. (2022)
    <doi:10.1080/10618600.2022.2104289>. Both models estimate subject-level 
    brain as deviations from known population-level networks, which are 
    estimated using standard ICA algorithms. Both models employ an 
    expectation-maximization algorithm for estimation of the latent brain 
    networks and unknown model parameters. Includes direct support for 'CIFTI',
    'GIFTI', and 'NIFTI' neuroimaging file formats.

Provides tools to work with template code and text in R. It aims to
    provide a simple substitution mechanism for R-expressions inside these
    templates. Templates can be written in other languages like 'SQL', can
    simply be represented by characters in R, or can themselves be R-expressions
    or functions.

Helper functions for MASCOTNUM / RT-UQ <https://uq.math.cnrs.fr/> algorithm template, for design of numerical experiments practice:
    algorithm template parser to support MASCOTNUM specification <https://github.com/MASCOTNUM/algorithms>, 
    'ask & tell' decoupling injection (inspired by <https://search.r-project.org/CRAN/refmans/sensitivity/html/decoupling.html>) 
    to use "crimped" algorithms (like uniroot(), optim(), ...) from outside R,
    basic template examples: Brent algorithm for 1 dim root finding and L-BFGS-B from base optim().