1 citations · 1 across the 7 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.LG2024
Causal Discovery on Dependent Binary Data
Alex Chen, Qing Zhou
The assumption of independence between observations (units) in a dataset is prevalent across various methodologies for learning causal graphical models. However, this assumption of…
stat.ML2024
Coordinated Multi-Neighborhood Learning on a Directed Acyclic Graph
Stephen Smith, Qing Zhou
Learning the structure of causal directed acyclic graphs (DAGs) is useful in many areas of machine learning and artificial intelligence, with wide applications. However, in the hig…