CREPO: An Open Repository to Benchmark Credal Network Algorithms
  Credal networks are a popular class of imprecise probabilistic graphical
models obtained as a Bayesian network generalization based on, so-called
credal, sets of probability mass functions. A Java library called CREMA has
been recently released to model, process and query credal networks. Despite the
NP-hardness of the (exact) task, a number of algorithms is available to
approximate credal network inferences. In this paper we present CREPO, an open
repository of synthetic credal networks, provided together with the exact
results of inference tasks on these models. A Python tool is also delivered to
load these data and interact with CREMA, thus making extremely easy to evaluate
and compare existing and novel inference algorithms. To demonstrate such
benchmarking scheme, we propose an approximate heuristic to be used inside
variable elimination schemes to keep a bound on the maximum number of vertices
generated during the combination step. A CREPO-based validation against
approximate procedures based on linearization and exact techniques performed in
CREMA is finally discussed.
