most citedA Hybrid Deep-Learning Model for El Niño Southern Oscillation in the Low-Data Regime

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cs.LG2026

Advancing Subseasonal Forecasting with Machine Learning

Hannah Guan, Soukayna Mouatadid, Paulo Orenstein +10

Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such forecasts enjoy unprecedented a…

cs.LG2024★ 1 cited

A Hybrid Deep-Learning Model for El Niño Southern Oscillation in the Low-Data Regime

Jakob Schloer, Matthew Newman, Jannik Thuemmel +2

While deep-learning models have demonstrated skillful El Niño Southern Oscillation (ENSO) forecasts up to one year in advance, they are predominantly trained on climate model simul…