  We present a numerical method to compute non-equilibrium memory kernels based
on experimental data or molecular dynamics simulations. The procedure uses a
recasting of the non-stationary generalized Langevin equation, in which we
expand the memory kernel in a series that can be reconstructed iteratively.
Each term in the series can be computed based solely on knowledge of the
two-time auto-correlation function of the observable of interest. As a proof of
principle, we apply the method to crystallization from a super-cooled Lennard
Jones melt. We analyze the nucleation and growth dynamics of crystallites and
observe that the memory kernel has a time extent that is about one order of
magnitude larger than the typical timescale needed for a particle to be
attached to the crystallite in the growth regime.
