Leon Barrett
Impact in
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Text Readability and Simplification
- Semantic Web and Ontologies
- Reinforcement Learning in Robotics
- Algorithms and Data Compression
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Semantic Web and Ontologies 1
- Natural Language Processing Techniques 1
- Bayesian Modeling and Causal Inference 1
- Logic, Reasoning, and Knowledge 1
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- Advanced Vision and Imaging 3
- Optical measurement and interference techniques 2
- Co-authors
- Dan Klein (1 shared paper)Slav Petrov (1 shared paper)Srini Narayanan (1 shared paper)Jerome A. Feldman (2 shared papers)Cindy Grimm (3 shared papers)Karan Singh (1 shared paper)Tom Erez (1 shared paper)
- Journals
- Neural Computation (1 paper)Open Scholarship Institutional Repository (Washington University in St. Louis) (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
Leon Barrett
6 papers receiving 602 citations
Leon Barrett's Hit Papers
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 605
- Computational Theory and Mathematics 63
- Computer Vision and Pattern Recognition 71
- Computer Graphics and Computer-Aided Design 11
- Software 7
Countries citing papers authored by Leon Barrett
This map shows the geographic impact of Leon Barrett'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 Leon Barrett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leon Barrett more than expected).
Fields of papers citing papers by Leon Barrett
This network shows the impact of papers produced by Leon Barrett. 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 Leon Barrett. The network helps show where Leon Barrett may publish in the future.
Co-authors
The 7 scholars most cited alongside Leon Barrett, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Learning accurate, compact, and interpretable tree annotation Hit paper breakdown → | 2006 | 547 |
| 2 | 2008 | 105 | |
| 3 | 2005 | 12 | |
| 4 | An architecture for structured, concurrent, real-time action | 2010 | 8 |
| 5 | 2008 | 8 | |
| 6 | 2007 | 1 | |
| 7 | 2011 | 0 |
About Leon Barrett
Leon Barrett is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Aerospace Engineering, Cognitive Neuroscience and Computational Theory and Mathematics, having authored 7 papers that have together received 681 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (3 papers), Robotics and Sensor-Based Localization (2 papers), Optical measurement and interference techniques (2 papers), Semantic Web and Ontologies (1 paper), Natural Language Processing Techniques (1 paper), Image Processing Techniques and Applications (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Logic, Reasoning, and Knowledge (1 paper). The work is most often cited by research in Artificial Intelligence (605 citations), Computational Theory and Mathematics (63 citations), Computer Vision and Pattern Recognition (71 citations), Computer Graphics and Computer-Aided Design (11 citations) and Software (7 citations). Leon Barrett has collaborated with scholars based in United States and Canada. Frequent co-authors include Dan Klein, Slav Petrov, Srini Narayanan, Jerome A. Feldman, Cindy Grimm, Karan Singh and Tom Erez. Their work appears in journals such as Neural Computation and Open Scholarship Institutional Repository (Washington University in St. Louis).
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.