J. Pearl

1.3k citations
28 papers · 628 · h-index 14

Impact in

Papers in

J. Pearl

26 papers receiving 579 citations

Peers

J. Pearl
Comparison fields: 5 of 100
  • Signal Processing 166
  • Statistics and Probability 86
  • Computer Vision and Pattern Recognition 149
  • Artificial Intelligence 186
  • Applied Mathematics 51
Replace H. Späth with:
H. Späth Germany
A. J. Lawrance United Kingdom
William S. Meisel United States
Pedro A. Morettin Brazil
Mudassir Uddin United Kingdom
David W. Scott
Vladas Pipiras United States
W. L. Nicholson United States
Yaming Yu United States
Jean‐Marc Azäis France
J. Pearl relative to H. Späth Germany H. Späth's profile →
Citations per field
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H. Späth · 1×
Citations per year

Countries citing papers authored by J. Pearl

Since Specialization
Citations

This map shows the geographic impact of J. 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 J. Pearl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Pearl more than expected).

Fields of papers citing papers by J. Pearl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. 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 J. Pearl. The network helps show where J. Pearl may publish in the future.

Co-authors

The 18 scholars most cited alongside J. Pearl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with J. Pearl Line = papers co-authored together J. Pearl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015118
2 201493
3 197678
4 197369
5 197237
6
Conditional independence and its representations
199028
7 199028
8 197122
9
Bayesian decision methods
199021
10
Bayesian and belief-functions formalisms for evidential reasoning: a conceptual analysis
199018
11 199617
12 200716
13 197514
14 197113
15 19759
16 19769
17 19758
18 19735
19 19795
20 19764

About J. Pearl

J. Pearl is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Signal Processing, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 28 papers that have together received 628 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (4 papers), Bayesian Modeling and Causal Inference (4 papers), Digital Filter Design and Implementation (4 papers), Matrix Theory and Algorithms (3 papers), Mathematical Analysis and Transform Methods (3 papers), Topic Modeling (3 papers), Algorithms and Data Compression (3 papers) and Advanced Algebra and Logic (2 papers). The work is most often cited by research in Signal Processing (166 citations), Statistics and Probability (86 citations), Computer Vision and Pattern Recognition (149 citations), Artificial Intelligence (186 citations) and Applied Mathematics (51 citations). J. Pearl has collaborated with scholars based in United States, Israel and Australia. Frequent co-authors include Manabu Kuroki, Michael Ghil, Philippe Naveau, Alexis Hannart, Harry Andrews, William K. Pratt, Dan Geiger, Mark Hopkins, Arthur L. Delcher and Adam J. Grove. Their work appears in journals such as IEEE Transactions on Information Theory, Gastroenterology, Quantum, Journal of Artificial Intelligence Research and Journal of Logic and Computation.

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.

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