Robert M. Patton
Impact in
- Artificial Intelligence top 5%
- 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
-
- Neural Networks and Reservoir Computing 10
- Machine Learning and Data Classification 5
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- Advanced Neural Network Applications 8
- Co-authors
- Steven R. YoungThomas E. PotokDerek RoseThomas P. KarnowskiSeung–Hwan LimCatherine D. SchumanJ. Parker MitchellPrasanna Date
- Journals
- D-Lib Magazine (3 papers)Scientific American (1 paper)Journal of Medical Systems (1 paper)Frontiers in Neuroscience (1 paper)Quantitative Science Studies (1 paper)
- Partner nations
- United StatesUnited KingdomChile
In The Last Decade
Robert M. Patton
61 papers receiving 827 citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Artificial Intelligence 447
- Computer Vision and Pattern Recognition 153
- Structural Biology 8
- Computational Theory and Mathematics 72
- Electrical and Electronic Engineering 248
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 4 | |
| 3 | 2021 | 19 | |
| 4 | 2021 | 9 | |
| 5 | 2021 | 2 | |
| 6 | 2021 | 3 | |
| 7 | FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. | 2020 | 2 |
| 8 | 2019 | 46 | |
| 9 | 2019 | 1 | |
| 10 | 2019 | 3 | |
| 11 | 2019 | 14 | |
| 12 | 2017 | 6 | |
| 13 | 2017 | 30 | |
| 14 | 2016 | 7 | |
| 15 | 2015 | 1 | |
| 16 | 2009 | 1 | |
| 17 | Discovery, analysis, and characteristics of event impacts | 2008 | 1 |
| 18 | 2006 | 2 | |
| 19 | Agent Based Approach for Searching, Mining and Managing Enormous Amounts of Spatial Image Data | 2005 | 1 |
| 20 | 1951 | 35 |
About Robert M. Patton
Robert M. Patton is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Structural Biology, Ecological Modeling and Medical Laboratory Technology, having authored 67 papers that have together received 865 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (16 papers), Ferroelectric and Negative Capacitance Devices (13 papers), Neural Networks and Reservoir Computing (10 papers), Advanced Neural Network Applications (8 papers), Complex Network Analysis Techniques (7 papers), Biomedical Text Mining and Ontologies (6 papers), Neural dynamics and brain function (5 papers) and Machine Learning and Data Classification (5 papers). The work is most often cited by research in Artificial Intelligence (447 citations), Computer Vision and Pattern Recognition (153 citations), Structural Biology (8 citations), Computational Theory and Mathematics (72 citations) and Electrical and Electronic Engineering (248 citations). Robert M. Patton has collaborated with scholars based in United States, United Kingdom and Chile. Frequent co-authors include Steven R. Young, Thomas E. Potok, Derek Rose, Thomas P. Karnowski, Seung–Hwan Lim, Catherine D. Schuman, J. Parker Mitchell, Prasanna Date, James S. Plank and Maryam Parsa. Their work appears in journals such as D-Lib Magazine, Scientific American, Journal of Medical Systems, Frontiers in Neuroscience 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.