Optimize Your Sampling: Tuned Diffusion Sampling with Bayesian Optimization

Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive.

Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive. While much work has focused on efficient solvers and samplers, comparatively little attention has been paid to selecting the…