Generalization Dynamics of Linear Diffusion Models
The study analyzes how hierarchical data structure affects linear diffusion models' generalization when training data is finite. It identifies two regimes based on sample size versus dimension and shows that regularization and hierarchy influence learning speed and overfitting mitigation, confirming that a more hierarchical covariance spectrum leads to better model fits.