AI RESEARCH
Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems
arXiv CS.LG
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ArXi:2603.08311v1 Announce Type: cross We study identifiability in continuous-time linear stationary stochastic differential equations with known causal structure. Unlike existing approaches, we relax the assumption of a known diffusion matrix, thereby respecting the model's intrinsic scale invariance. Rather than recovering drift coefficients themselves, we