@inproceedings{64d60df1a4454418b6554c3d744c39a6,
title = "Quantitative Analysis of Nonlinear Multifidelity Optimization for Inverse Electrophysiology",
abstract = "Reliable cardiac excitation predictions depend not only on accurate geometric and physiological models, usually formulated as PDEs, and our ability to solve those faithfully, but also on the model{\textquoteright}s correct parameterization.",
author = "Fatemeh Chegini and Alena Kopani{\v c}{\'a}kov{\'a} and Martin Weiser and Rolf Krause",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 26th International Conference on Domain Decomposition Methods, 2020 ; Conference date: 07-12-2020 Through 12-12-2020",
year = "2022",
doi = "10.1007/978-3-030-95025-5_6",
language = "English (US)",
isbn = "9783030950248",
series = "Lecture Notes in Computational Science and Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "67--78",
editor = "Brenner, {Susanne C.} and Axel Klawonn and Jinchao Xu and Eric Chung and Jun Zou and Felix Kwok",
booktitle = "Domain Decomposition Methods in Science and Engineering XXVI",
address = "Germany",
}