SLAM compares two spatial labelings by turning them into weighted graphs, extracting edge-type distributions, and measuring distributional discrepancy with sliced Wasserstein distances and maximum mean discrepancy.
Objective criteria for the evaluation of clustering methods.Journal of the Ameri- can Statistical association, 66(336):846–850,
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A Methodological Framework for Measuring Spatial Labeling Similarity
SLAM compares two spatial labelings by turning them into weighted graphs, extracting edge-type distributions, and measuring distributional discrepancy with sliced Wasserstein distances and maximum mean discrepancy.