DESCRIPTION

Package: gpflowr
Type: Package
Title: Gaussian Process Modelling Using TensorFlow
Version: 0.1.1
Date: 2017-04-30
Authors@R: c(
	person("Nick", "Golding", role = c("aut", "cre"), email = "nick.golding.research@gmail.com")
	)
Description: A port of the GPflow python package to R. gpflowr implements
    Gaussian process models using Google's TensorFlow library (via the tensorflow
    R package). This enables automatic gradient construction via symbolic
    differentiation, efficient linear algebra, and portability to CPUs, GPUs, and
    across platforms. Like tensorflow, this package requires installation of python
    and TensorFlow.
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
URL: https://github.com/goldingn/gpflowr
BugReports: https://github.com/goldingn/gpflowr/issues
SystemRequirements: Python (>= 2.7.0) with header files and shared library;
    TensorFlow (https://www.tensorflow.org/);
    GPflow (https://github.com/GPflow/GPflow)
Imports:
    reticulate (>= 0.7.0.9001)
Suggests:
    testthat
RoxygenNote: 6.0.1