# forward sampling for Bayesian network with continuous variables and equation-based causal relationships

I have a physical system which can be represented by the following Bayesian network.

It has the following characteristics

1)

The encoded variables are continuous variables

2)
The causal relationships between different variables are equations. For instance, x5 = f(x1, x2, x3).

In the standard Bayesian network, we can use Gibbs sampling or MCMC to do the forward sampling. For this kind of Bayesian network, how to perform the forward sampling.