AI RESEARCH
The Generalised Kernel Covariance Measure
arXiv CS.LG
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ArXi:2604.03721v1 Announce Type: cross We consider the problem of conditional independence (CI) testing and adopt a kernel-based approach. Kernel-based CI tests embed variables in reproducing kernel Hilbert spaces, regress their embeddings on the conditioning variables, and test the resulting residuals for marginal independence. This approach yields tests that are sensitive to a broad range of conditional dependencies.