Use information gain to evaluate generative models on their ability to estimate uncertainty correctly, not just prediction accuracy.
This paper introduces a better way to evaluate AI models that generate synthetic biological images (virtual staining). Instead of just checking if the overall results look right, it measures whether the model correctly estimates uncertainty about what it's predicting for each individual cell.