Robert M. Patton
Impact in
- Artificial Intelligence top 2%
- Neural Networks and Reservoir Computing
- Quantum Computing Algorithms and Architecture
- Machine Learning and Data Classification
- Neural Networks and Applications
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- Advanced Neural Network Applications
Papers in
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- Neural Networks and Reservoir Computing 12
- Neural Networks and Applications 6
- Machine Learning and Data Classification 5
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- Advanced Neural Network Applications 8
- Co-authors
- Thomas E. Potok (55 shared papers)Steven R. Young (16 shared papers)Catherine D. Schuman (24 shared papers)Derek C. Rose (6 shared papers)Thomas P. Karnowski (3 shared papers)Seung–Hwan Lim (7 shared papers)J. Parker Mitchell (8 shared papers)Prasanna Date (8 shared papers)
- Journals
- D-Lib Magazine (3 papers)Frontiers in Neuroscience (1 paper)ACM Journal on Emerging Technologies in Computing Systems (1 paper)Quantum Information Processing (1 paper)Quantitative Science Studies (1 paper)
- Partner nations
- United StatesUnited KingdomCzechia
In The Last Decade
Robert M. Patton
73 papers receiving 1.0k citations
Robert M. Patton's Hit Papers
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 573
- Computer Vision and Pattern Recognition 191
- Computational Theory and Mathematics 103
- Structural Biology 8
- Software 23
Countries citing papers authored by Robert M. Patton
This map shows the geographic impact of Robert M. Patton'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 Robert M. Patton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert M. Patton more than expected).
Fields of papers citing papers by Robert M. Patton
This network shows the impact of papers produced by Robert M. Patton. 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 Robert M. Patton. The network helps show where Robert M. Patton may publish in the future.
Co-authors
The 25 scholars most cited alongside Robert M. Patton, 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 83 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Optimizing deep learning hyper-parameters through an evolutionary algorithm Hit paper breakdown → | 2015 | 325 |
| 2 | 2020 | 74 | |
| 3 | 2019 | 53 | |
| 4 | 2018 | 52 | |
| 5 | 2020 | 40 | |
| 6 | 2017 | 37 | |
| 7 | 1951 | 36 | |
| 8 | 2020 | 27 | |
| 9 | 2020 | 23 | |
| 10 | 2017 | 22 | |
| 11 | 2018 | 22 | |
| 12 | 2021 | 21 | |
| 13 | 2018 | 20 | |
| 14 | 2003 | 19 | |
| 15 | 2019 | 16 | |
| 16 | 2019 | 16 | |
| 17 | 2018 | 16 | |
| 18 | 2021 | 15 | |
| 19 | 2008 | 14 | |
| 20 | 2016 | 13 |
About Robert M. Patton
Robert M. Patton is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Information Systems and Signal Processing, having authored 83 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (19 papers), Ferroelectric and Negative Capacitance Devices (15 papers), Neural Networks and Reservoir Computing (12 papers), Complex Network Analysis Techniques (9 papers), Advanced Neural Network Applications (8 papers), Biomedical Text Mining and Ontologies (8 papers), Neural Networks and Applications (6 papers) and Machine Learning and Data Classification (5 papers). The work is most often cited by research in Artificial Intelligence (573 citations), Computer Vision and Pattern Recognition (191 citations), Computational Theory and Mathematics (103 citations), Structural Biology (8 citations) and Software (23 citations). Robert M. Patton has collaborated with scholars based in United States, United Kingdom and Czechia. Frequent co-authors include Thomas E. Potok, Steven R. Young, Catherine D. Schuman, Derek C. Rose, Thomas P. Karnowski, Seung–Hwan Lim, J. Parker Mitchell, Prasanna Date, Maryam Parsa and James S. Plank. Their work appears in journals such as D-Lib Magazine, Frontiers in Neuroscience, ACM Journal on Emerging Technologies in Computing Systems, Quantum Information Processing and Quantitative Science Studies.
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.