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Convergence of the training and validation loss. The CRB-loss converges to approximately 1, which corresponds to the loss of a maximally efficient unbiased estimator, while the MSE-loss converges to a value that provides little insight in the performance of the network. The two curves result from separate networks trained with respective loss function.
