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Surrogate‐Assisted Bayesian Inference of Fracture Network Parameters From Elastic Waves: A Sensitivity‐Guided Approach
Department of Geology Ghent University Ghent Belgium;Faculty of Civil Engineering and Geosciences Delft University of Technology Delft The Netherlands.ORCID iD: 0000-0002-0820-0774
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air, Water and Landscape Sciences. Department of Earth Sciences Uppsala University Uppsala Sweden.ORCID iD: 0000-0002-3990-4707
School of Resources and Safety Engineering Central South University Changsha China.ORCID iD: 0000-0002-0908-1009
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air, Water and Landscape Sciences. Department of Earth Sciences Uppsala University Uppsala Sweden.
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2026 (English)In: Journal of Geophysical Research: Machine Learning and Computation, ISSN 2993-5210, Vol. 3, no 4, article id e2025JH001201Article in journal (Refereed) Published
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2026. Vol. 3, no 4, article id e2025JH001201
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Geotechnical Engineering and Engineering Geology Geophysics Multidisciplinary Geosciences
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URN: urn:nbn:se:uu:diva-594482DOI: 10.1029/2025jh001201OAI: oai:DiVA.org:uu-594482DiVA, id: diva2:2087275
Available from: 2026-07-20 Created: 2026-07-20 Last updated: 2026-07-20

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Zhang, LeLei, QinghuaDong, LongjunHermans, Thomas
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