TL;DR本文介绍了一种基于 Markov 过程的 mean field variational approximation 方法，用于近似描述 Continuous-time Bayesian networks 中的概率分布，并提供了较好的推断和学习效果。
Abstract
continuous-time bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact representation, inference in such