A differentiable information imbalance optimization automatically identifies dynamical communities and constructs a community causal graph from high-dimensional time series in linear-in-tests time.
To level out the fluctuation ranges of different variables, we first scale each variable by its standard de- viation over the entire trajectory
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Linear scaling causal discovery from high-dimensional time series by dynamical community detection
A differentiable information imbalance optimization automatically identifies dynamical communities and constructs a community causal graph from high-dimensional time series in linear-in-tests time.