Bigger is not Always Better: Scaling Properties of Latent Diffusion
Models
Bigger is not Always Better: Scaling Properties of Latent Diffusion
Models
We study the scaling properties of latent diffusion models (LDMs) with an emphasis on their sampling efficiency. While improved network architecture and inference algorithms have shown to effectively boost sampling efficiency of diffusion models, the role of model size -- a critical determinant of sampling efficiency -- has not been …