For high-dimensional data with less information per effective variable, diffusion tends to be a sensible approach empirically.

“just use that. And but ultimately you can have all both of these solve the same type of problem. It's just whether you do the decomposition in the observable space, whether you do the decomposition in the latent space and for things like hi for high dimensional things”

“which then sounds of less information per effective per variable it it tends to make sense or at least empirically tends to make sense to go into diffusion instead”