Lianglong Li

CUTS+: High-Dimensional Causal Discovery from Irregular Time-Series

Causal discovery in time-series is a fundamental problem in the machine learning community, enabling causal reasoning and decision-making in complex scenarios. Recently, researchers successfully discover causality by combining neural networks with Granger causality, but their performances degrade la…