Search Results for author: Mark K. Transtrum

Found 5 papers, 4 papers with code

The supremum principle selects simple, transferable models

no code implementations21 Sep 2021 Cody Petrie, Christian Anderson, Casie Maekawa, Travis Maekawa, Mark K. Transtrum

We consider how mathematical models enable predictions for conditions that are qualitatively different from the training data.

Model Selection

Maximizing the information learned from finite data selects a simple model

2 code implementations2 May 2017 Henry H. Mattingly, Mark K. Transtrum, Michael C. Abbott, Benjamin B. Machta

We use the language of uninformative Bayesian prior choice to study the selection of appropriately simple effective models.

Information topology identifies emergent model classes

1 code implementation22 Sep 2014 Mark K. Transtrum, Gus Hart, Peng Qiu

We introduce Information Topology in analogy with information geometry as characterizing the "abstract model" of which statistical models are realizations.

Data Analysis, Statistics and Probability Materials Science Statistics Theory Statistics Theory

Improvements to the Levenberg-Marquardt algorithm for nonlinear least-squares minimization

3 code implementations27 Jan 2012 Mark K. Transtrum, James P. Sethna

We introduce several improvements to the Levenberg-Marquardt algorithm in order to improve both its convergence speed and robustness to initial parameter guesses.

Data Analysis, Statistics and Probability Computational Physics

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