Author

Kun Zhang

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Preprint Aug 2026

Testing the Validity of Instrumental Variable Sets in Causal Additive Models with Non-Constant Effects

Instrumental variable (IV) methods are powerful for causal effect estimation with unmeasured confounding, but in practice researchers often face a set of candidate IVs whose validity is difficult to determine from observational data. This paper studies the problem of testing the validity of IV sets under Causal Additiv...

Xi-Chen Guo, Feng Xie, Bingbing Tang et al. · 0 citations

#machine learning Preprint May 2026

Learning beyond Site Bias for OOD Generalization in Brain Networks

First, CORE estimates site-specific confounder effects and aggregates the resulting deconfounders by cross-source reliability for unseen-site correction, while extracting a population scaffold of reproducible label-associated connections from site-wise residualized FC.

Ying-Xu Wang, Kun Zhang, Yan-Wu Yang et al. · 2 citations