Noè, U., Chen, W. W., Filippone, M., Hill, N. and Husmeier, D. (2017) Inference in a Partial Differential Equations Model of Pulmonary Arterial and Venous Blood Circulation using Statistical Emulation. In: 13th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, Stirling, UK, 01-03 Sep 2016, pp. 184-198. ISBN 9783319678337 (doi: 10.1007/978-3-319-67834-4_15)
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Abstract
The present article addresses the problem of inference in a multiscale computational model of pulmonary arterial and venous blood circulation. The model we consider is a computationally expensive simulator of physiological processes which, given specific parameter values, solves a system of nonlinear partial differential equations and returns predicted pressure and flow values at different locations in the arterial and venous blood vessels. The standard approach in parameter calibration for computer codes is to emulate the simulator using a Gaussian Process (GP) prior. In the present work, we take a different approach and emulate the objective function itself, i.e. the residual sum of squares between the simulations and the observed data. We demonstrate that this modified emulator achieves a reduction in the computational costs of inference by two orders of magnitude (from 8 hours to 3 minutes CPU time).
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Hill, Professor Nicholas and Noe, Mr Umberto and Husmeier, Professor Dirk and Chen, WeiWei |
Authors: | Noè, U., Chen, W. W., Filippone, M., Hill, N., and Husmeier, D. |
College/School: | College of Science and Engineering > School of Mathematics and Statistics |
ISSN: | 0302-9743 |
ISBN: | 9783319678337 |
Published Online: | 17 October 2017 |
Copyright Holders: | Copyright © 2017 Springer International Publishing AG |
First Published: | First published in Lecture Notes in Computer Science 10477: 184-198 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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