A very different paradigm to inference and graphic model, is the use of whats called sampling or particle based methods, in those methods rather than trying to manipulate the exponentially, even infinitely large probability distribution as a whole we randomly sample, instan-, instances from that distributions and then use those instances as a sparse representation we can use those instances then to estimate various quantities that we care about regarding the statistics of the overall distribution, before we show how this is use in the context of graphical models, let's  go ahead and see how it's applied in a simple setting. 