304 citations · 1.5k across the 44 of their papers we have counts for
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Bayesian, frequentist, and information geometric approaches to parametric uncertainty quantification of classical empirical interatomic potentials
Yonatan Kurniawan, Cody L. Petrie, Kinamo J. Williams +5
In this paper, we consider the problem of quantifying parametric uncertainty in classical empirical interatomic potentials (IPs) using both Bayesian (Markov Chain Monte Carlo) and…
Information geometry for multiparameter models: New perspectives on the origin of simplicity
Katherine N. Quinn, Michael C. Abbott, Mark K. Transtrum +2
Complex models in physics, biology, economics, and engineering are often sloppy, meaning that the model parameters are not well determined by the model predictions for collective b…
The supremum principle selects simple, transferable models
Cody Petrie, Christian Anderson, Casie Maekawa +2
We consider how mathematical models enable predictions for conditions that are qualitatively different from the training data. We propose techniques based on information topology t…