Reviews: Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models

Neural Information Processing Systems 

Summary The paper presents a method for assessing the uncertainty in the evaluation of an expectation over the output of a complex simulation model given uncertainty in the model parameters. Such simulation models take a long time to solve, given a set of parameters, so the task of averaging over the outputs of the simulation given uncertainty in the parameters is challenging. One cannot simply run the model so many times that error in the estimate of the integral is controlled. The authors approach the problem as an inference task. Given samples from the parameter posterior one must infer the posterior over the integral of interest.