Functional Causal Model Discovery
Functional Causal Model Discovery is a methodological framework within causal discovery that identifies causal relationships by modeling each variable as a deterministic function of its direct causes and an independent noise term, distinguishing itself from purely probabilistic or constraint-based approaches through its explicit functional form assumptions.
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433
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15
Institutions
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2017–2026
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On Estimation of Functional Causal Models
Kun Zhang, Zhikun Wang, Jiji Zhang et al. · ACM Transactions on Intelligent Systems and Technology · 2015 · 42 citations
Quantitative Analysis of Genetic and Neuronal Multi-Perturbation Experiments
Alon Kaufman, Alon Keinan, Isaac Meilijson et al. · PLoS Computational Biology · 2005 · 34 citations · Full text
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Radboud University Nijmegen
Nijmegen, The Netherlands
1 h-index
1 publications
64 citations
Max Planck Institute for Intelligent Systems
Stuttgart, Germany
1 h-index
3 publications
126 citations

Tel Aviv University
Tel Aviv, Israel
1 h-index
4 publications
136 citations
Southwest University
Chongqing, China
1 h-index
2 publications
82 citations

Foshan University
Foshan, China
1 h-index
1 publications
20 citations
Hebrew University of Jerusalem
Jerusalem, Israel
1 h-index
1 publications
34 citations
Singapore Institute of Technology
Singapore, Singapore
1 h-index
1 publications
20 citations
Huawei Technologies (China)
Shenzhen, China
1 h-index
1 publications
28 citations
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Repository · 1 publications · 64 citations
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1 publications · 34 citations
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1 publications · 41 citations
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Repository · 1 publications · 27 citations
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AJS · 1 publications · 165 citations
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