Schematic of the neural network architecture we used to predict 2D spatially resolved maps of the ex situ stellar mass fraction from observable 2D maps of stellar mass density, velocity, and velocity dispersion. A diffusion model is trained to learn the underlying distribution of ex situ maps using the MaNGIA training set, conditioned on the corresponding observable maps (after a series of preprocessing steps; for details, see Section 3.3).