Figure 8.

A non-Gaussian pdf that is conditionally Gaussian. More specifically, when knowing $x^1$, $x^2$ can be approximated by a Gaussian pdf. Notice $x^1$ can be a bi-modal, non-Gaussian distribution if $x^2$ is given, e.g., for $x^2=0$.