Active Causal Discovery

Active Causal Discovery is a methodological framework within causal discovery that actively selects and intervenes on variables in the system to iteratively acquire data that maximally inform the identification of causal structures, distinguishing itself from passive observational approaches by enabling targeted experimentation to reduce uncertainty in causal model estimation.

2

Publications

45

Citations

15

Authors

2

Institutions

Publications per year

2017–2026

2

Authors

15

  1. NS
    Nino Scherrer

    1 publications · 16 citations

    1

    h-index

  2. OB
    Olexa Bilaniuk

    University of Ottawa, Canada

    1 publications · 16 citations

    1

    h-index

  3. AG
    Anirudh Goyal

    Université de Montréal, Canada

    1 publications · 16 citations

    1

    h-index

  4. BS
    Bernhard Schölkopf

    Max Planck Institute for Intelligent Systems, Germany

    1 publications · 16 citations

    1

    h-index

  5. NR
    Nan Rosemary Ke

    Université de Montréal, Canada

    1 publications · 16 citations

    1

    h-index

1–5 of 15

Venues

  1. Energy

    1 publications · 29 citations

    1

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 16 citations

    1

    h-index

  3. Tunnelling and Underground Space Technology

    1 publications · 18 citations

  4. Scientific Reports

    1 publications · 12 citations

1–4