1. A computer implemented method for evaluating performances of generative models, comprising: receiving data describing observations associated with observable variables of a first generative model and a second generative model, each of the first and second generative models having information about relationships among one or more variables; for at least one observation: applying the first generative model to the observation to produce a first assessment of the observation; applying the second generative model to the observation to produce a second assessment of the observation; and determining, using one or more processors, a similarity score between the first and second assessments; and outputting a subset of the observations, each corresponding to first and second assessments having a similarity score that is less than a predetermined threshold.