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One Intervention per Component is Enough: Towards Identifiability in Linear Stochastic Dynamics from Steady State
We study the problem of recovering the parameters of a multivariate Ornstein-Uhlenbeck (OU) process from steady-state observational and interventional data. In many applications, such as large-scale gene perturbation experiments, only stationary "snapshot" measurements are available, making standard
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