Variational Gaussian Process Diffusion Processes

arXiv:2306.02066v3 Announce Type: replace
Abstract: Diffusion processes are a class of stochastic differential equations (SDEs) providing a rich family of expressive models that arise naturally in dynamic modelling tasks. Probabilistic inference and learning under generative models with latent processes endowed with a non-linear diffusion process prior are intractable problems. We build upon work within variational inference, approximating the posterior process as a linear diffusion process, and point out pathologies in the approach. We propose an alternative parameterization of the Gaussian …

abstract arxiv build class cs.lg differential diffusion dynamic family generative generative models inference linear modelling non-linear prior process processes stat.ml stochastic tasks type work