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Vidya Samadi
Clemson UniversityMeeting roles in:
Evaluating Machine Learning Methods for River Flow Time Series Modeling in U.S. Midwest Agricultural Watersheds
NeuralSWWM Python Package: A Hybrid Hydrologic-Machine Learning Algorithm for Stormwater Management
NeuralFAO56: Leveraging Neural Network for data driven FAO56-Based Irrigation Demand Estimation
Understanding Distributed Sensing Instruments for Scientific Discovery: A Guided Tour Through the Tools of Earth Science Poster
The Role of Uncertainty Quantification Algorithms in Deep Neural Network Models for Flood Prediction
WaterSoftHack: Machine Learning, Data Analytics and Cyberinfrastructure Training for Water Science and Engineering
How AI Partnerships Work in Hydrologic Simulation?
Harnessing Large Language Models to Reason About Extreme Weather Conditions
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