55 citations · 138 across the 9 of their papers we have counts for
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cs.LG2024
Global atmospheric data assimilation with multi-modal masked autoencoders
Thomas J. Vandal, Kate Duffy, Daniel McDuff +2
Global data assimilation enables weather forecasting at all scales and provides valuable data for studying the Earth system. However, the computational demands of physics-based alg…
physics.ao-ph2024★ 43 cited
Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting
Puja Das, August Posch, Nathan Barber +6
Precipitation nowcasting, critical for flood emergency and river management, has remained challenging for decades, although recent developments in deep generative modeling (DGM) su…