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cs.LG2024★ 2 cited
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…
cs.LG2024
PAC Learnability under Explanation-Preserving Graph Perturbations
Xu Zheng, Farhad Shirani, Tianchun Wang +4
Graphical models capture relations between entities in a wide range of applications including social networks, biology, and natural language processing, among others. Graph neural…
cs.LG2023★ 1 cited
HurriCast: Synthetic Tropical Cyclone Track Generation for Hurricane Forecasting
Shouwei Gao, Meiyan Gao, Yuepeng Li +1
The generation of synthetic tropical cyclone(TC) tracks for risk assessment is a critical application of preparedness for the impacts of climate change and disaster relief, particu…