Creativity of Diffusion Models: A Mathematical Explanation from Google Research
Google researchers have shown that the ability of diffusion models to generate new data, rather than simply memorizing the training set, is a mathematical consequence of smoothing the score function during neural network training. Smoothing forces the model to interpolate between data points, creating new, plausible samples.
Google/DeepMind




