Causal discovery in non-stationary time series data is crucial for understanding complex systems but remains challenging due to evolving relationships over time. This paper presents a novel two-stage ...

Temporal Knowledge Graphs (TKGs) are being widely explored to predict the future for they record multi-relational knowledge and the happening time of real-life facts. Existing works learn sequential ...