Conditional Variational Diffusion Models

arXiv:2312.02246v4 Announce Type: replace-cross
Abstract: Inverse problems aim to determine parameters from observations, a crucial task in engineering and science. Lately, generative models, especially diffusion models, have gained popularity in this area for their ability to produce realistic solutions and their good mathematical properties. Despite their success, an important drawback of diffusion models is their sensitivity to the choice of variance schedule, which controls the dynamics of the diffusion process. Fine-tuning this schedule for specific applications is crucial but time-costly …

abstract aim arxiv cs.ai cs.cv cs.lg diffusion diffusion models engineering generative generative models good parameters science sensitivity solutions stat.ml success type