Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences
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This map shows the geographic impact of Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences more than expected).
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This network shows the impact of Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Integrating Deep Learning Into an Energy Framework for Rapid Regional Damage Assessment and Fragility Analysis Under Mainshock‐Aftershock Sequences.
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This paper is also available at doi.org/10.1002/eqe.4331.