3 papers
cs.LG2026
Earth System World Model for What-If Simulations: A Case Study for Terrestrial Ecosystems
Zhihao Wang, Ruichen Wang, Ruohan Li +6
Machine learning emulators have become essential for accelerating expensive Earth-system simulations, but most existing approaches remain passive forecasters: they reproduce simula…
cs.CE2025
Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses
Bolin Shen, Eren Erman Ozguven, Yue Zhao +3
Florida is particularly vulnerable to hurricanes, which frequently cause substantial economic losses. While prior studies have explored specific contributors to hurricane-induced d…
cs.CL2025
TyphoFormer: Language-Augmented Transformer for Accurate Typhoon Track Forecasting
Lincan Li, Eren Erman Ozguven, Yue Zhao +3
Accurate typhoon track forecasting is crucial for early system warning and disaster response. While Transformer-based models have demonstrated strong performance in modeling the te…