activity
20232026
most citedTowards an end-to-end artificial intelligence driven global weather forecasting system

10 citations · 10 across the 10 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

nlin.CD2026

Koopman early warning signals for bifurcation and rate-induced tipping

Juan Nathaniel, Carla Roesch, Derek DeSantis +5

Abrupt transitions in complex systems are often preceded by early warning signals. However, most indicators rely on the notion of critical slowing down and do not generally extend…

cs.LG2026

In-context learning to predict critical transitions in dynamical systems

Yunus Sevinchan, Juan Nathaniel, Kai Ueltzhöffer +8

Critical transitions - abrupt, often irreversible changes in system dynamics - arise across human and natural systems, often with catastrophic consequences. Real-world observations…

cs.AI2026

WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain

Yi Xiao, Qilong Jia, Hang Fan +4

Many decisions in complex terrain require fast wind estimates at specific locations and heights rather than dense forecasts on fixed grids. We present WindINR, a latent-state impli…

cs.CV2026

Earth-o1: A Grid-free Observation-native Atmospheric World Model

Junchao Gong, Kaiyi Xu, Wangxu Wei +22

Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…

cs.LG2026

Accurate and Efficient Hybrid-Ensemble Atmospheric Data Assimilation in Latent Space with Uncertainty Quantification

Hang Fan, Juan Nathaniel, Yi Xiao +5

Data assimilation (DA) combines model forecasts and observations to estimate the optimal state of the atmosphere with its uncertainty, providing initial conditions for weather pred…