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stat.ML2026
Measuring Differences between Conditional Distributions using Kernel Embeddings
Peter Moskvichev, Siu Lun Chau, Dino Sejdinovic
Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. While proposed methods for meas…
stat.ML2026
The Generalised Kernel Covariance Measure
Luca Bergen, Dino Sejdinovic, Vanessa Didelez
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, regr…