Attention‐Based Reconstruction of Full‐Field Tsunami Waves From Sparse Tsunameter Networks

Abstract We investigate the potential of an attention‐based neural network architecture, the Senseiver, for sparse sensing in tsunami forecasting. Specifically, we focus on the Tsunami Data Assimilation Method, which generates forecasts from tsunameter networks. Our model is used to reconstruct high...

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Autori principali:	Edward McDugald, Arvind Mohan, Darren Engwirda, Agnese Marcato, Javier E. Santos
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Wiley 2025-08-01
Serie:	Geophysical Research Letters
Soggetti:	sparse sensing tsunami forecasting attention mechanism deep learning tsunami data assimilation
Accesso online:	https://doi.org/10.1029/2025GL115345
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