AI RESEARCH
BGM-IV: an AI-powered Bayesian generative modeling approach for instrumental variable analysis
arXiv CS.AI
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ArXi:2605.07029v1 Announce Type: cross Instrumental-variable (IV) regression enables causal estimation under endogeneity, but modern IV problems often involve nonlinear structural effects and high-dimensional covariates. Existing nonlinear IV methods directly learn the causal relation in observed feature space or rely on learned representations within two-stage or moment-based procedures, which can struggle when the causal information is embedded in a high-dimensional representation.