3 papers
cs.LG2026
Multi-Quantile Regression for Extreme Precipitation Downscaling
Hamed Najafi, Gareth Lagerwall, Jayantha Obeysekera +1
Deep super-resolution networks for precipitation downscaling achieve strong bulk skill yet systematically under-predict the heavy-tail events that drive flood risk. We demonstrate…
cs.LG2025
Uncovering Insights of Compound Flooding with Data-Driven AI
Xu Zheng, Chaohao Lin, Sipeng Chen +7
Compound flooding, driven by nonlinear interactions between multiple hydrometeorological factors, poses a significant challenge to hazard prevention. Existing forecasting approache…
cs.LG2024
TimeX++: Learning Time-Series Explanations with Information Bottleneck
Zichuan Liu, Tianchun Wang, Jimeng Shi +7
Explaining deep learning models operating on time series data is crucial in various applications of interest which require interpretable and transparent insights from time series s…