Identifiability from Stationary Covariance in Linear SDEs with Reciprocal Interactions and Latent Variables
Continuous-time stochastic differential equations (SDEs) provide a natural framework for modeling interacting dynamical systems. A central causal question is whether causal effects among observed variables can be identified from observational data drawn from the stationary distribution, given the underlying causal graph. For linear SDEs, existing identifiability results are largely restricted to fully observed systems whose causal graphs contain no directed 2-cycles. We first establish new graphical conditions for the generic identifiability of causal effects in systems that may contain directed 2-cycles, thereby allowing for reciprocal interactions. Next, we address the previously unexpl...
| Authors | Ana Leticia Garcez Vicente, Saber Salehkaleybar |
|---|---|
| Primary category | cs.LG |
| Published | 22 October 2026 |
| Last updated at source | 22 October 2026 |
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