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Dapeng Feng
Stanford UniversityMeeting roles in:
Capturing the spatial variability of plant hydraulics at continental scale using differentiable modelling.
Why and Where Physics-Machine Learning Integration Matters for Hydrologic Modeling
Determining the Relative Influence of Water Potential, Biomass, and Temperature on Vegetation Optical Depth
A daily, long-term, microwave remote sensing-informed dataset of live fuel moisture content from machine learning
Global Reach Scale Hydrology: Progress and Challenges
Global High-Resolution Hydrologic Simulation to Enhance Predictions in Ungauged Regions with Hybrid Differentiable Models
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