Optimal Control and Optimal Experimental Design for MRI and Photoacoustic Imaging (MBAI)
Associated Publications
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Multi-type sensor placement for PDE-based Bayesian inverse problems,
2026
bibtex
@ONLINE{MaioAlexanderianKovalNicholson:2026:1, AUTHOR = {Maio, Steven and Alexanderian, Alen and Koval, Karina and Nicholson, Ruanui}, DATE = {2026-07}, EPRINT = {2607.08074}, EPRINTTYPE = {arXiv}, TITLE = {Multi-type sensor placement for PDE-based Bayesian inverse problems}, } -
Non-intrusive optimal experimental design for large-scale nonlinear Bayesian inverse problems using a Bayesian approximation error approachJournal of Scientific Computing 104(3), 2025
bibtex
@ARTICLE{KovalNicholson:2025:1, AUTHOR = {Koval, Karina and Nicholson, Ruanui}, PUBLISHER = {Springer Science and Business Media LLC}, DATE = {2025-08}, DOI = {10.1007/s10915-025-03008-7}, EPRINT = {2405.07412}, EPRINTTYPE = {arXiv}, JOURNALTITLE = {Journal of Scientific Computing}, NUMBER = {3}, TITLE = {Non-intrusive optimal experimental design for large-scale nonlinear Bayesian inverse problems using a Bayesian approximation error approach}, VOLUME = {104}, } -
Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging,
2025
bibtex
@ONLINE{CuiKovalHerzogScheichl:2025:1, AUTHOR = {Cui, Tiangang and Koval, Karina and Herzog, Roland and Scheichl, Robert}, DATE = {2025-02}, EPRINT = {2502.20086}, EPRINTTYPE = {arXiv}, TITLE = {Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging}, } -
Tractable optimal experimental design using transport mapsInverse Problems 40(12), 2024
bibtex
@ARTICLE{KovalHerzogScheichl:2024:2, AUTHOR = {Koval, Karina and Herzog, Roland and Scheichl, Robert}, PUBLISHER = {IOP Publishing}, DATE = {2024-10}, DOI = {10.1088/1361-6420/ad8260}, EPRINT = {2401.07971}, EPRINTTYPE = {arXiv}, JOURNALTITLE = {Inverse Problems}, NUMBER = {12}, PAGES = {125002}, TITLE = {Tractable optimal experimental design using transport maps}, VOLUME = {40}, }