Latent Schr{\"o}dinger Bridge Diffusion Model for Generative Learning

arXiv:2404.13309v1 Announce Type: cross
Abstract: This paper aims to conduct a comprehensive theoretical analysis of current diffusion models. We introduce a novel generative learning methodology utilizing the Schr{\"o}dinger bridge diffusion model in latent space as the framework for theoretical exploration in this domain. Our approach commences with the pre-training of an encoder-decoder architecture using data originating from a distribution that may diverge from the target distribution, thus facilitating the accommodation of a large sample size through the utilization of pre-existing …

abstract analysis arxiv bridge cs.lg current decoder diffusion diffusion model diffusion models domain encoder encoder-decoder exploration framework generative methodology novel paper pre-training space stat.ml training type