Causal Graph Search

Causal Graph Search is a methodological framework within causal inference that systematically identifies directed acyclic graphs representing plausible causal relationships from observational or experimental data by distinguishing causal structures through conditional independence tests or score-based optimization.

33

Publications

1.9K

Citations

401

Authors

137

Institutions

Publications per year

2017–2026

16

Authors

401

  1. SZ
    Shengyu Zhu

    Huawei Technologies (China), China

    3 publications · 155 citations

    3

    h-index

  2. RS
    Richard Scheines

    Carnegie Mellon University, United States

    2 publications · 82 citations

    2

    h-index

  3. IN
    Ignavier Ng

    Huawei Technologies (China), China

    2 publications · 118 citations

    2

    h-index

  4. PS
    Peter Spirtes

    Carnegie Mellon University, United States

    2 publications · 145 citations

    2

    h-index

  5. ZC
    Zhitang Chen

    Huawei Technologies (China), China

    2 publications · 126 citations

    2

    h-index

1–5 of 401

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 157 citations

    4

    h-index

  2. 2

    h-index

  3. Journal of Artificial Intelligence Research

    JAIR · 1 publications · 60 citations

    1

    h-index

  4. The Quarterly Review of Economics and Finance

    QREF · 1 publications · 253 citations

    1

    h-index

  5. Työväentutkimus Vuosikirja

    1 publications · 41 citations

    1

    h-index

1–5