In causal inference, one approach to defining the complexity of a candidate generative model is to restrict the explicit class of admissible mechanisms. In this approach, all causal mechanisms $\hat{f}$ belonging to a particular class $\mathcal{F}$ of bivariate functional causal models (FCM) are assumed to be simple, while all others are considered complex. For these methods, the model complexity term is assigned as $C_{\hat{B}}(\theta) = 0$ if $\hat{f} \in \mathcal{F}$, and $C_{\hat{B}}(\theta) = 1$ otherwise.