Causal Discovery

Individual Causal Structure Learning from Population Data

Learning the causal structure of each individual plays a crucial role in neuroscience, biology, and so on. Existing methods consider …

Wei Chen, Xiaokai Huang, Zijian Li, Ruichu Cai, Zhiyi Huang, Zhifeng Hao

Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants

Causal discovery with latent variables is a crucial but challenging task. Despite the emergence of numerous methods aimed at addressing …

Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang

Causal Discovery with Latent Confounders Based on Higher-Order Cumulants

Causal discovery with latent confounders is an important but challenging task in many scientific areas. Despite the success of some …

Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang

Causal-learn is a python package for causal discovery that implements both classical and state-of-the-art causal discovery algorithms, which is a Python translation and extension of Tetrad.