70 citations
- Leipzig UniversityDE2 papers
- Peking UniversityCN2 papers
- University of FloridaUS2 papers
- Adolfo Ibáñez UniversityCL1 paper
- Arizona State UniversityUS1 paper
- Beijing University of Civil Engineering and ArchitectureCN1 paper
- Budapest University of Technology and EconomicsHU1 paper
- California Institute of TechnologyUS1 paper
- California State University, FullertonUS1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Chiba UniversityJP1 paper
- China Agricultural UniversityCN1 paper
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cs.LG2025★ 4 cited
RegionGCN: Spatial-Heterogeneity-Aware Graph Convolutional Networks
Hao Guo, Han Wang, Di Zhu +3
Modeling spatial heterogeneity in the data generation process is essential for understanding and predicting geographical phenomena. Despite their prevalence in geospatial tasks, ne…
cs.LG2024★ 10 cited
Recurrent Neural Networks for Modelling Gross Primary Production
David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6
Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest atmosphere-to-land CO flux, especi…