Instability-guided perturbations in the Aurora AI model can induce downstream shifts in an atmospheric river's moisture transport, potentially lowering landfall intensity in a California case study.
Exebench: Benchmarking foundation models on extreme earth events
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SHRUG-FM fuses geophysical OOD detection, embedding-space OOD detection, and predictive uncertainty via a shallow decision tree to let foundation models abstain from unreliable outputs on burn scar, flood, and landslide tasks.
citing papers explorer
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Instability-Aware Steering of an Extreme Atmospheric River in an AI Weather Foundation Model
Instability-guided perturbations in the Aurora AI model can induce downstream shifts in an atmospheric river's moisture transport, potentially lowering landfall intensity in a California case study.
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SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation
SHRUG-FM fuses geophysical OOD detection, embedding-space OOD detection, and predictive uncertainty via a shallow decision tree to let foundation models abstain from unreliable outputs on burn scar, flood, and landslide tasks.