  A prescription is presented for the interpolation between multi-dimensional
distribution templates based on one or multiple model parameters. The technique
uses a linear combination of templates, each created using fixed values of the
model's parameters and transformed according to a specific procedure, to model
a non-linear dependency on model parameters and the dependency between them. By
construction the technique scales well with the number of input templates used,
which is a useful feature in modern day particle physics, where a large number
of templates is often required to model the impact of systematic uncertainties.
