For models using the variance of predictions of a 5 model ensemble, each model was trained on the mean-squared error (MSE) of the predicted labels and the true labels of the test set, and only differed between other members of the ensemble by having a different random seed for weight initialization. The loss function for the Gaussian regression models (µ,σ 2 ) is the log-likelihood of the true label (y) as shown in Equation .