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Session
Presentation | H43N: Machine Learning and Data Assimilation for Terrestrial Hydrologic Modeling and Discovery I Poster
Poster
H43N-1721: Coping with Data Scarcity in Extreme Flood Forecasting: A Deep Generative Modeling Approach
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Schedule
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Credits
Thu, Dec 18
Board 1721‚ Hall EFG (Poster Hall)
2:15pm - 5:45pm (Central)
NOLA CC
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Ali Sattari
University of Alabama
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Author(s):
Ali Sattari
, University of Alabama
(First Author, Presenting Author)
Hamid Moradkhani
, The University of Alabama
View Abstract
Scientific Discipline
Hydrology
Suggested Itineraries
Disasters‚ Calamities and Extreme Events
Machine Learning and AI
Neighborhood
Earth Covering
Type
Poster
I Will Be at My Poster Time
View This Poster
Main Session
Poster
H43N: Machine Learning and Data Assimilation for Terrestrial Hydrologic Modeling and Discovery I Poster
2:15pm-5:45pm Dec 18 (Central)
Lijing Wang
Discussion
