Judea Pearl
Impact in
- Statistics and Probability top 0.01%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Artificial Intelligence top 0.01%
- Bayesian Modeling and Causal Inference
- AI-based Problem Solving and Planning
- Logic, Reasoning, and Knowledge
Papers in
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- Bayesian Modeling and Causal Inference 152
- Logic, Reasoning, and Knowledge 34
- AI-based Problem Solving and Planning 26
- Machine Learning and Algorithms 22
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- Advanced Causal Inference Techniques 90
- Statistical Methods and Inference 38
- Statistical Methods and Bayesian Inference 22
- Statistical Methods in Clinical Trials 18
- Co-authors
- Christopher Hitchcock (1 shared paper)Rina Dechter (13 shared papers)James M. Robins (3 shared papers)Sander Greenland (2 shared papers)Elias Bareinboim (20 shared papers)Itay Meiri (3 shared papers)Thomas Verma (5 shared papers)Henry E. Kyburg (1 shared paper)
- Journals
- Artificial Intelligence (22 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (6 papers)Sociological Methods & Research (4 papers)Biometrika (4 papers)International Journal of Approximate Reasoning (4 papers)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Judea Pearl
268 papers receiving 38.3k citations
Judea Pearl's Hit Papers
Peers
Comparison fields: 5 of 237
- Statistics and Probability 6.7k
- Artificial Intelligence 19.4k
- General Decision Sciences 577
- Management Science and Operations Research 3.8k
- Signal Processing 2.8k
Countries citing papers authored by Judea Pearl
This map shows the geographic impact of Judea Pearl's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Judea Pearl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Judea Pearl more than expected).
Fields of papers citing papers by Judea Pearl
This network shows the impact of papers produced by Judea Pearl. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Judea Pearl. The network helps show where Judea Pearl may publish in the future.
Co-authors
The 25 scholars most cited alongside Judea Pearl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 271 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference Hit paper breakdown → | 1988 | 10317 |
| 2 | Causality Hit paper breakdown → | 2009 | 6016 |
| 3 | Causality: Models, Reasoning and Inference Hit paper breakdown → | 2001 | 3227 |
| 4 | Causal Diagrams for Epidemiologic Research Hit paper breakdown → | 1999 | 2691 |
| 5 | Causal diagrams for empirical research Hit paper breakdown → | 1995 | 1441 |
| 6 | Fusion, propagation, and structuring in belief networks Hit paper breakdown → | 1986 | 1339 |
| 7 | Causal inference in statistics: An overview Hit paper breakdown → | 2009 | 1318 |
| 8 | Temporal constraint networks Hit paper breakdown → | 1991 | 1161 |
| 9 | Generalized best-first search strategies and the optimality of A* Hit paper breakdown → | 1985 | 711 |
| 10 | Confounding and Collapsibility in Causal Inference Hit paper breakdown → | 1999 | 594 |
| 11 | Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Hit paper breakdown → | 1991 | 539 |
| 12 | An Introduction to Causal Inference Hit paper breakdown → | 2010 | 437 |
| 13 | 2005 | 359 | |
| 14 | Causal inference and the data-fusion problem Hit paper breakdown → | 2016 | 351 |
| 15 | 1997 | 345 | |
| 16 | 1987 | 341 | |
| 17 | The seven tools of causal inference, with reflections on machine learning Hit paper breakdown → | 2019 | 329 |
| 18 | The Book of Why: The New Science of Cause and Effect Hit paper breakdown → | 2018 | 317 |
| 19 | 1997 | 304 | |
| 20 | A Theory of Inferred Causation. | 1991 | 295 |
About Judea Pearl
Judea Pearl is a scholar working on Artificial Intelligence, Statistics and Probability, Management Science and Operations Research, Computer Networks and Communications and Computational Theory and Mathematics, having authored 271 papers that have together received 41.6k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (152 papers), Advanced Causal Inference Techniques (90 papers), Statistical Methods and Inference (38 papers), Logic, Reasoning, and Knowledge (34 papers), AI-based Problem Solving and Planning (26 papers), Machine Learning and Algorithms (22 papers), Statistical Methods and Bayesian Inference (22 papers) and Statistical Methods in Clinical Trials (18 papers). The work is most often cited by research in Statistics and Probability (6.7k citations), Artificial Intelligence (19.4k citations), General Decision Sciences (577 citations), Management Science and Operations Research (3.8k citations) and Signal Processing (2.8k citations). Judea Pearl has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Christopher Hitchcock, Rina Dechter, James M. Robins, Sander Greenland, Elias Bareinboim, Itay Meiri, Thomas Verma, Henry E. Kyburg, Joseph Y. Halpern and Alexander Balke. Their work appears in journals such as Artificial Intelligence, IEEE Transactions on Pattern Analysis and Machine Intelligence, Sociological Methods & Research, Biometrika and International Journal of Approximate Reasoning.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.