2023
Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy
ICML 2023poster
Kernelized Stein discrepancy (KSD) is a score-based discrepancy widely used in goodness-of-fit tests. It can be applied even when the target distribution has an unknown normalising factor, such as in Bayesian analysis. We show theoretically and empirically that the KSD test can suffer from low power…