Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

Understand

Diffusion models that can generate high-quality data from randomly sampled Gaussian noises have become the mainstream generative method in both academia and industry.

• Are randomly sampled Gaussian noises equally good for diffusion models? While a large body of works tried to understand and improve diffusion models, previous works overlooked the possibility to select or optimize the sampled noise the possibility of selecting or optimizing sampled noises for improving diffusion models.
• In this paper, we mainly made three contributions.
• First, we report that not all noises are created equally for diffusion models.