1 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
The Power of Explainability in Forecast-Informed Deep Learning Models for Flood Mitigation
Jimeng Shi, Vitalii Stebliankin, Giri Narasimhan
Floods can cause horrific harm to life and property. However, they can be mitigated or even avoided by the effective use of hydraulic structures such as dams, gates, and pumps. By…
Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates
Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang +2
Floods can be very destructive causing heavy damage to life, property, and livelihoods. Global climate change and the consequent sea-level rise have increased the occurrence of ext…
Engineering an algorithm for constructing low-stretch geometric graphs with near-greedy average-degrees
FNU Shariful, Justin Weathers, Anirban Ghosh +1
We design and engineer Fast-Sparse-Spanner, a simple and practical (fast and memory-efficient) algorithm for constructing sparse low stretch-factor geometric graphs on large points…