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Conditional Kernel Stein Discrepancy

arXiv:2610.11863v1 Announce Type: new Abstract: Kernel Stein discrepancies (KSDs) provide a versatile tool for comparing distributions. One of their main applications is in quantifying the goodness-of-fit (GoF) between a data-generating distribution and a prescribed target distribution. In this wor…

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  1. 2026-10-09 04:00 · arXiv stat.ML
    Conditional Kernel Stein Discrepancy

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