DCD: Decomposition-based Causal Discovery from Autocorrelated and Non-Stationary Temporal Data

Multivariate time series in domains such as finance, climate science, and healthcare often exhibit long-term trends, seasonal patterns, and short-term fluctuations, complicating causal inference under non-stationarity and autocorrelation. Existing causal discovery methods typically operate on raw ob