The orbits of stars in a galaxy can reveal information about its past. In particular, orbital structures give us information about previous merger processes between galaxies. Finding these structures from astronomical observations is an ill-posed problem, which amplifies measurement noise.
However, orbital structures can be observed for simulated galaxies, in which individual stars can be tracked. We propose a projection-based method to use these simulated data as a learning set that allows us to regularize the problem.