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An unsupervised objective is derived that learns structural properties of a representation map and theoretical results connecting its minimization to tangent-space recovery are established, while an autoencoder baseline shows that small map-first errors can still produce substantial violations of the targeted propertie...
Accurate and continuous global ocean wind data are crucial for understanding weather and climate patterns. However, gaps in observations often limit the availability of measured ocean wind maps. As an emerging remote sensing technique, spaceborne global navigation satellite system reflectometry (GNSS-R) platforms have...
OceanBench is a benchmark designed to evaluate and accelerate global short-range data-driven ocean forecasting, constructed from a curated dataset comprising first-guess trajectories, nowcasts, and atmospheric forcings from operational physical ocean models, typically unavailable in public datasets due to assimilation...
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