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Relative Wasserstein Spatial Depth for Cluster Number Selection in Distributional Data
Contemporary data in many scientific domains, such as images, media streams, biomedical omics, are naturally modeled as probability distributions in Wasserstein space instead of points in Euclidean space. Consequently, clustering methods for distributions are in high demand, as they provide explorat
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