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stat.ML2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso
Danru Xu, Erdun Gao, Wei Huang +3
Learning the underlying Bayesian Networks (BNs), represented by directed acyclic graphs (DAGs), of the concerned events from purely-observational data is a crucial part of evidenti…
cs.LG2022★ 11 cited
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models
Erdun Gao, Ignavier Ng, Mingming Gong +5
State-of-the-art causal discovery methods usually assume that the observational data is complete. However, the missing data problem is pervasive in many practical scenarios such as…