2 papers
stat.ML2026
Domain-Adapted Diffusion Models for Conditional Independence Testing
Yanfeng Yang, Junda Zhao, Yijie Gao +8
Conditional independence (CI) is a fundamental concept in statistics and machine learning. Recent advances in conditional generative modeling provide flexible tools for generative-…
cs.LG2026
Fast Flow Matching based Conditional Independence Tests for Causal Discovery
Shunyu Zhao, Yanfeng Yang, Shuai Li +1
Constraint-based causal discovery methods require a large number of conditional independence (CI) tests, which severely limits their practical applicability due to high computation…