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. 2023 Jan 12;13:630. doi: 10.1038/s41598-023-27738-6

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Left panels, the true unseen models velocity models (top panel from population L, bottom from population T) used to generate the input seismograms for the FNO network. Middle panels, the velocity model predictions (outputs from the FNO). Right panel, profiles through the true and predicted models. The seismic source location is highlighted by the asterisks. In the FNO output, the source location is also predicted by the network. Both velocity models here are each recovered from input data associated with only one randomly located shot into 10 randomly located surface receivers, each.