Predicting nucleation using machine learning in the Ising model

Machine learning has been successfully applied to a number of physics problems, but the method works less well for a system that is near a critical point. An application to nucleation in the two-dimensional Ising model shows that as the spinodal is approached and the densities of the nucleating droplet and the background become similar, the method is less accurate.