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Paul Stoy
University of Wisconsin MadisonMeeting roles in:
Near real-time prediction of the coupled carbon and water cycles
ALIVE-KGML: A Knowledge-Guided Machine Learning Framework for Coupled Carbon and Water Flux Estimation from Geostationary Satellites
Enhancing Forest Flux Predictions with Foliar Traits
BenchFlux: Scalable AI Benchmarks for Terrestrial Carbon Fluxes to Advance Research, Education, and Resource Management
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