triepels/cgraph: Computational Graphs

Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various operations including basic arithmetic, trigonometry operations, and linear algebra operations. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.

Getting started

Package details

AuthorRon Triepels
MaintainerRon Triepels <[email protected]>
LicenseApache License 2.0
Version3.0.1
URL https://cgraph.org/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("triepels/cgraph")
triepels/cgraph documentation built on Nov. 20, 2018, 2:25 a.m.