I have successfully implemented a hill climbing approach to Bayesian structure learning using a Gaussian Bayesian network. I want to now implement a more sophisticated model with latent variables. However, information on this topic seems very scarce. If I google Bayesian networks, there is an abundance of resources, but almost none for applications of latent variables to BNs.
Can latent variables be used in Bayesian networks? If so, is there an accepted introductory textbook or set of lectures notes that people commonly consult to learn about this? I'm confused why this is hard to find information on. Is it uncommon to do use latent variables with Bayesian networks? If so, why? Are there better alternative methods?
So far, I've been able to find information on hidden Markov random fields, such as
This is the kind of thing I'm looking for, but I want it specifically for Bayesian networks.
The closest I've found for hidden Bayesian networks has been