It is known that solving an exact inference problem on a discrete Bayesian network with many deterministic nodes can be far cheaper than what would be expected based on its treewidth. In this article, we introduce a novel technique for this: to the operations of factor multiplication and factor summation that form the basis of many inference algorithms, we add factor indexing. We integrate this operation into variable elimination, and extend the minweight heuristic accordingly. A preliminary empirical evaluation gives promising results.
['Sander Evers', 'Peter J. F. Lucas']
Marginalization without summation: exploiting determinism in factor algebra