  In this article we present an emulation strategy for one-loop matrix
elements. This strategy is based on the factorisation properties of matrix
elements and is an extension of the work presented in arXiv:2107.06625. We show
that a percent-level accuracy can be achieved even for large multiplicity
processes. The point accuracy obtained is such that it dwarfs the statistical
accuracy of the training sample which allows us to use our model to augment the
size of the training set by orders of magnitude without additional evaluations
of expensive one-loop matrix elements.
