Maximizing the information learned from finite data selects a simple model

Henry H. Mattingly, Mark K. Transtrum, Michael C. Abbott +1

We use the language of uninformative Bayesian prior choice to study the selection of appropriately simple effective models. We advocate for the prior which maximizes the mutual inf…