I was wondering whether it is possible to convert a Bayesian network into several different forms of factor graphs but still hold the same conditional probability from the original Bayesian Network. So that we can still do inference through message passing on the factor graph.
From Figure below, my intuition is that we can transform (or recalculate / redistribute) the conditional probability tablesfrom the bayesian network into all factor nodes on the converted factor graphs. But I'm not sure how to do the calculations.
So can anyone help me with this problem, possibly with examples of conditional probability tables to the factor nodes on those graphs?
Thanks for help and advice...
