1 citations · 1 across the 3 of their papers we have counts for
4 papers
Using Heteroscedasticity for Causal Discovery under Hidden Confounding
Jing Zou, Wei Li, Wei Lin
The presence of hidden confounding in observational studies poses a fundamental challenge to the identification and estimation of causal structures encoded by directed acyclic grap…
Assumption-lean Inference for Network-linked Data
Wei Li, Nilanjan Chakraborty, Robert Lunde
We consider statistical inference for network-linked regression problems, where covariates may include network summary statistics computed for each node. In settings involving netw…
Semiparametric Causal Discovery and Inference with Invalid Instruments
Jing Zou, Wei Li, Wei Lin
Learning causal relationships among a set of variables, as encoded by a directed acyclic graph, from observational data is complicated by the presence of unobserved confounders. In…
Discovery and inference of possibly bi-directional causal relationships with invalid instrumental variables
Wei Li, Rui Duan, Sai Li
Learning causal relationships between pairs of complex traits from observational studies is of great interest across various scientific domains. However, most existing methods assu…