Don't know where your data is from? Bayesian modeling for unknown coordinates

A technical walkthrough applies Bayesian spatial probability models to geologic sampling problems where coordinate data is uncertain or sparse. The method leverages spatial correlation in drill-hole data without requiring full geophysical models. Relevant to ML practitioners working on geostatistics, kriging, or sparse sensor fusion problems, though the content appears truncated with no benchmark results presented.