Our goal is to close this gap and propose a simple and effective comparison tool between two DNNs based on their test set score distributions.
we make four contributions: Defining a DNN comparison framework: We define three criteria that a DNN comparison tool should meet: (a) Since we observe only a sample from the population score distribution of each model, the decision should be significant under well justified statistical assumptions.