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Research questionHow can differentiable causal discovery override wrong edge priors while preserving directional identifiability?A forbidden-edge prior can suppress a true causal edge before data-driven relaxation reacts. Separately, correlation matching can make opposite directions equally costly by discarding variance information.
Machine Learning
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Guide, Not Bind: Why Defeasible Priors Fail in Augmented Lagrangian Causal DiscoveryThe analysis concerns Augmented Lagrangian penalty-ramping, adaptive relaxation of forbidden-edge priors, and correlation- versus covariance-matching objectives in differentiable causal discovery. Evidence includes formal propositions and lemmas, plus 3,072 DADU training runs on graphs with 4–32 nodes; it does not establish a complete repair.research paper · Sep 3, 2026
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