Functional Neural Networks

A collection of functions which fit functional neural network models. In other words, this package will allow users to build deep learning models that have either functional or scalar responses paired with functional and scalar covariates. We implement the theoretical discussion found in Thind, Multani and Cao (2020) through the help of a main fitting and prediction function as well as a number of helper functions to assist with cross-validation, tuning, and the display of estimated functional weights.


Reference manual

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1.0 by Barinder Thind, a year ago,

Browse source code at

Authors: Richard Groenewald [ctb] , Barinder Thind [aut, cre, cph] , Jiguo Cao [aut] , Sidi Wu [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports keras, tensorflow, fda.usc, fda, ggplot2, ggpubr, caret, pbapply, reshape2, flux, doParallel, foreach, Matrix

Suggests knitr, rmarkdown

See at CRAN