AI RESEARCH
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations
arXiv CS.LG
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ArXi:2410.06128v4 Announce Type: replace Structural Causal Models (SCMs) offer a principled framework to reason about interventions and out-of-distribution generalization, which are key goals in scientific discovery. However, the task of learning SCMs from observed data poses formidable challenges, and often requires