Computer Science and Center for Research in Computer Vision
Speaker: Dr. Peng Wang From: University of Michigan Abstract Recent empirical studies have demonstrated that diffusion models can effectively learn the image distribution and generate new samples. Remarkably, these models can achieve this even with a small number of training samples despite a large image dimension, circumventing the curse of dimensionality. In this work, we provide theoretical insights into this …
CS/CRCV Seminars