We use priors in Bayesian networks to include prior knowledge in our models. In this context, what are these two terms:
-complicated prior -large scale prior
I have seen priors like Laplace, zero-mean Gaussian, Jaffery's or truncated Gaussian priors. However, the above two terms are new to me.
Can somebody point me towards a tutorial on this?