36 citations · 49 across the 20 of their papers we have counts for
4 papers · 1 filter
ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuning
Jimeng Shi, Azam Shirali, Giri Narasimhan
Extreme events are of great importance since they often represent impactive occurrences. For instance, in terms of climate and weather, extreme events might be major storms, floods…
CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantification
Jimeng Shi, Bowen Jin, Jiawei Han +2
Accurate weather forecasting is critical for science and society. Yet, existing methods have not managed to simultaneously have the properties of high accuracy, low uncertainty, an…
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…
FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation
Jimeng Shi, Zeda Yin, Arturo Leon +2
In coastal river systems, frequent floods, often occurring during major storms or king tides, pose a severe threat to lives and property. However, these floods can be mitigated or…