Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination.
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| Title: | Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination. |
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| Authors: | Agata R; Japan Agency for Marine-Earth Science and Technology, 3173-25, Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 2360001, Japan. agatar@jamstec.go.jp., Shiraishi K; Japan Agency for Marine-Earth Science and Technology, 3173-25, Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 2360001, Japan., Fujie G; Japan Agency for Marine-Earth Science and Technology, 3173-25, Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 2360001, Japan. |
| Source: | Scientific reports [Sci Rep] 2025 Jan 13; Vol. 15 (1), pp. 1846. Date of Electronic Publication: 2025 Jan 13. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2045-2322 |
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| DOI: | 10.1038/s41598-024-84995-9 |
