Due to the large flexibility of neural networks, training a model multiple times from different starting configurations yields slightly different predictions which can be assumed to approximately follow a Gaussian distribution. The following results will therefore be derived under the assumption that the committee predictions follow such a distribution. We first consider a committee of N C independently trained models with model variance as the only source of error. The committee will provide N C predictions ŷl (with l = 0, 1, ..., N C ), with mean ŷ and the committee standard deviation