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cs.LG2026
Latent Domain Modeling Improves Robustness to Geographic Shifts
Ruth Crasto, Esther Rolf
Geographic distribution shift arises when the distribution of locations on Earth in a training dataset is different from what is seen at inference time. Using standard empirical ri…
cs.LG2025
Mapping on a Budget: Optimizing Spatial Data Collection for ML
Livia Betti, Farooq Sanni, Gnouyaro Sogoyou +4
In applications across agriculture, ecology, and human development, machine learning with satellite imagery (SatML) is limited by the sparsity of labeled training data. While satel…