Graphical models are graphs in which nodes represent random variables, and the lack of arcs represent conditional independence assumptions. 

In undirected graphical models conditional independence is based on presence or absence of arc.

In directed graphical models conditional independence based on presence or absence of arc and the directionality of the arcs.

Dynamic Bayesian Networks (DBNs) are directed graphical models of stochastic processes.

HMMs are the simplest form of DBNs.