In contrast, our work makes use of the Bayesian nature of variational inference to estimate the uncertainty and learn from humans.
we sample variables from the prior network as the random perturbation to estimate the model uncertainty following the idea of Query-By-Committee (Seung et al., 1992) and optimize model parameters by maximizing the ELBO.