New publication in Nature Communications

Alexandre René’s paper “Selecting fitted models under epistemic uncertainty using a stochastic process on quantile functions” is now finally out in Nature Communications!

We are increasingly seeing data-driven methods used to fit scientific models, but methods to compare these models often underestimate relevant uncertainties, leading to overconfident comparisons. This paper examines how one can improve the quantification of uncertainties, especially those arise from modelling approximations or errors, and thus make statements about the most likely generative process underlying those data. The theory can be broadly applied to any type generative model, from graphs to neuroscience.