jingbin zhou

Influence without Confounding: Causal Discovery from Temporal Data with Long-term Carry-over Effects

Learning causal structures from temporal data is fundamental to many practical tasks, such as physical laws discovery and root causes localization. Real-world systems often exhibit long-term carry-over effects, where the value of a variable at the current time can be influenced by distant past va…