Puffin: Probabilistic Learning of Spatial Detail From Coarse Observations
PUFFIN uses high-resolution satellite embeddings to estimate fine-scale socioeconomic variables from coarse regional totals. It treats spatial disaggregation as probabilistic constraint satisfaction, learning a prior distribution for subregions and conditioning it on observed totals. This yields estimates that reproduce all published totals exactly while providing calibrated uncertainty.