CUED Publications database

Probabilistic models for integration error in the assessment of functional cardiac models

Oates, CJ and Niederer, S and Lee, A and Briol, FX and Girolami, M (2017) Probabilistic models for integration error in the assessment of functional cardiac models. In: UNSPECIFIED pp. 110-118..

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Abstract

This paper studies the numerical computation of integrals, representing estimates or predictions, over the output f(x) of a computational model with respect to a distribution p(dx) over uncertain inputs x to the model. For the functional cardiac models that motivate this work, neither f nor p possess a closed-form expression and evaluation of either requires ≈ 100 CPU hours, precluding standard numerical integration methods. Our proposal is to treat integration as an estimation problem, with a joint model for both the a priori unknown function f and the a priori unknown distribution p. The result is a posterior distribution over the integral that explicitly accounts for dual sources of numerical approximation error due to a severely limited computational budget. This construction is applied to account, in a statistically principled manner, for the impact of numerical errors that (at present) are confounding factors in functional cardiac model assessment.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: UNSPECIFIED
Depositing User: Cron Job
Date Deposited: 23 Mar 2020 20:02
Last Modified: 08 Apr 2021 05:44
DOI: