A New AI Research From MIT Reduces Variance in Denoising Score-Matching, Improving Image Quality, Stability, and Training Speed in Diffusion Models

Diffusion models have recently produced outstanding results on various generating tasks, including the creation of images, 3D point clouds, and molecular conformers. Ito stochastic differential equations (SDE) are a unified framework that can incorporate these models. The models acquire knowledge of time-dependent score fields through score-matching, which later directs the reverse SDE during generative sampling. … Continue reading A New AI Research From MIT Reduces Variance in Denoising Score-Matching, Improving Image Quality, Stability, and Training Speed in Diffusion Models