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Phu Nguyen
University of California IrvineMeeting roles in:
Advances in Machine Learning for Earth Science: Observation, Modeling, and Applications I Poster
Performance of Satellite-Derived Precipitation Products over the Santa Ana River Basin for Reservoir Operations at Prado Dam
Spatial Assessment of Two Satellite Rainfall Products Using Quality Controlled Ground-Based Interpolation in Saudi Arabia: Revealing the Need for Regional Bias Correction
Advances in Machine Learning for Earth Science: Observation, Modeling, and Applications II Oral
Leveraging Passive Microwave Data (MiRS) With U-Net Architecture for Satellite Rainfall Estimation in High-Latitude Regions: A Case Study over Alaska
Advances in Machine Learning for Earth Science: Observation, Modeling, and Applications III Oral
Regional Kilometer-Scale Data-Driven Precipitation Forecasting over the Western United States Using Artificial Intelligence (AI)
PUnet-CDR: A Deep Learning Framework for Reconstructing High-Resolution Global Precipitation Climate Data Records
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