Animation of observed trajectories using spline-based interpolation (see for example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. (2016), <doi:10.1111/2041-210X.12465> "A functional model for characterizing long-distance movement behaviour". Methods Ecol Evol). Intended to be used exploratory data analysis, and perhaps for preparation of presentations.

Obtain network structures from animal GPS telemetry observations and 
    statistically analyse them to assess their adequacy for social network analysis. Methods include 
    pre-network data permutations, bootstrapping techniques to obtain confidence intervals 
    for global and node-level network metrics, and correlation and regression analysis of the local network metrics.

Animate Shiny and R Markdown content when it comes into view using 'animate-css' effects thanks to 'jQuery AniView'.

Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors. Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors.

Training of neural networks for classification and regression tasks
    using mini-batch gradient descent. Special features include a function for 
    training autoencoders, which can be used to detect anomalies, and some 
    related plotting functions. Multiple activation functions are supported, 
    including tanh, relu, step and ramp. For the use of the step and ramp 
    activation functions in detecting anomalies using autoencoders, see 
    Hawkins et al. (2002) <doi:10.1007/3-540-46145-0_17>. Furthermore, 
    several loss functions are supported, including robust ones such as Huber 
    and pseudo-Huber loss, as well as L1 and L2 regularization. The possible 
    options for optimization algorithms are RMSprop, Adam and SGD with momentum.
    The package contains a vectorized C++ implementation that facilitates 
    fast training through mini-batch learning.

A 'reticulate' wrapper for the Python package 'anndata'.
    Provides a scalable way of keeping track of data and learned
    annotations.  Used to read from and write to the h5ad file format.