Causal Inference From Data

Causal Inference From Data is a systematic methodology within data interpretation that identifies and establishes cause-and-effect relationships among variables by distinguishing genuine causal mechanisms from mere correlations through formal modeling, controlled assumptions, and statistical or algorithmic analysis.

823

Publications

92.4K

Citations

1.7K

Authors

703

Institutions

Publications per year

2017–2026

338

Authors

1.7K

  1. DJ
    Dominik Janzing

    Max Planck Institute for Intelligent Systems, Germany

    20 publications · 2.2K citations

    17

    h-index

  2. BS
    Bernhard Schölkopf

    Max Planck Institute for Intelligent Systems, Germany

    19 publications · 2.4K citations

    16

    h-index

  3. JP
    Judea Pearl

    University of California, Los Angeles, United States

    18 publications · 7.8K citations

    15

    h-index

  4. CG
    Clark Glymour

    Carnegie Mellon University, United States

    14 publications · 1.5K citations

    14

    h-index

  5. JM
    Joris M. Mooij

    Radboud University Nijmegen, Netherlands

    10 publications · 1.7K citations

    10

    h-index

1–5 of 1.7K

Venues

  1. arXiv (Cornell University)

    Repository · 59 publications · 2.6K citations

    24

    h-index

  2. Journal of the American Statistical Association

    15 publications · 7.6K citations

    14

    h-index

  3. Sociological Methods & Research

    SMR · 14 publications · 1.5K citations

    14

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 365 citations

    11

    h-index

  5. Epidemiology

    11 publications · 7.4K citations

    11

    h-index

1–5