Summary Causal Graph
Summary causal graphs represent a simplified view of complex dynamic systems, focusing on causal relationships between time series variables without specifying the temporal lag between them. Current research emphasizes identifying direct and total causal effects from these graphs, even in the presence of latent confounders and cycles, using both graphical criteria and adjustment sets to enable estimation from observational data. This work is significant because it allows causal inference in situations where complete temporal causal graphs are unavailable or impractical to obtain, improving our ability to understand and model complex systems in various domains.
Papers
October 31, 2024
June 9, 2024
October 23, 2023
June 29, 2023
March 7, 2023