Adding location-based weights to conformal prediction yields per-location uncertainty intervals; the authors test this on housing and temperature data but the coverage proof is incomplete.
Also, the residuals {Ο΅ππ}ππβπΌπΌπ‘π‘π‘π‘π‘π‘πππ‘π‘ on one of this training sets will be obtained
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GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction
Adding location-based weights to conformal prediction yields per-location uncertainty intervals; the authors test this on housing and temperature data but the coverage proof is incomplete.