Photo by Tiffany Tertipes on UnsplashOn uncertainty-penalized Bayesian information criterionAuthors: Pongpisit Thanasutives, Ken-ichi FukuiAbstract: The uncertainty-penalized information criterion (UBIC) has been proposed as a brand new mannequin-choice criterion for information-pushed partial differential equation (PDE) discovery. In this paper, we present that utilizing the UBIC is equal to using the standard BIC to a set of overparameterized fashions derived from the potential regression fashions of various complexity measures. The end result signifies that the asymptotic property of the UBIC and BIC holds indifferently. △
https://medium.com/@monocosmo77/research-on-bayesian-information-criterion-part1-machine-learning-2024-eb86070bd163