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Quantification of Model Uncertainty

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FHTW01 - Uncertainty quantification for cardiac models

Statistical estimation and uncertainty quantification of parameter values within models is fairly well established, where Bayesian and non-Bayesian approaches typically show broad agreement. In contrast, quantification of uncertainty around issues of model choice or parameter selection is much more contentious. We will review some of the distinctive features of statistical approaches to model evaluation with a focus on the foundations of Bayesian inference and robustness to model misspecification.

This talk is part of the Isaac Newton Institute Seminar Series series.

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