AI RESEARCH
Bayesian Hierarchical Invariant Prediction
arXiv CS.AI
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ArXi:2505.11211v3 Announce Type: replace-cross We propose Bayesian Hierarchical Invariant Prediction (BHIP) reframing Invariant Causal Prediction (ICP) through the lens of Hierarchical Bayes. We leverage the hierarchical structure to explicitly test invariance of causal mechanisms under heterogeneous data, resulting in improved computational scalability for a larger number of predictors compared to ICP. Moreover, given its Bayesian nature BHIP enables the use of prior information.