Barry L. Kalman
- Artificial Intelligence top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics
- Co-authors
- Stan C. KwasnyJames W. RichardsonDouglas F. CoveyWilliam R. ReinusJames A. FerrendelliWilliam E. KlunkAnthony WilsonAndrew F. Laine
- Topics
- Neural Networks and Applications (9 papers)Molecular spectroscopy and chirality (3 papers)Machine Learning and ELM (2 papers)
- Partner nations
- United States
In The Last Decade
Barry L. Kalman
19 papers receiving 315 citations
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 109
- Molecular Biology 51
- Computer Vision and Pattern Recognition 47
- Electrical and Electronic Engineering 45
- Atomic and Molecular Physics, and Optics 37
Countries citing papers authored by Barry L. Kalman
This map shows the geographic impact of Barry L. Kalman'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 Barry L. Kalman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barry L. Kalman more than expected).
Fields of papers citing papers by Barry L. Kalman
This network shows the impact of papers produced by Barry L. Kalman. 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 Barry L. Kalman. The network helps show where Barry L. Kalman may publish in the future.
Co-authorship network of co-authors of Barry L. Kalman
This figure shows the co-authorship network connecting the top 25 collaborators of Barry L. Kalman. A scholar is included among the top collaborators of Barry L. Kalman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Barry L. Kalman. Barry L. Kalman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 126 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 13 | |
| 5 | 9 | |
| 6 | 5 | |
| 7 | 17 | |
| 8 | 32 | |
| 9 | 1 | |
| 10 | Distributed Patterns as Hierarchical Structures | 3 |
| 11 | 1 | |
| 12 | Choosing a Sigmoidal Function | 2 |
| 13 | 5 | |
| 14 | 7 | |
| 15 | 42 | |
| 16 | 5 | |
| 17 | 21 | |
| 18 | 31 | |
| 19 | 7 |
About Barry L. Kalman
Barry L. Kalman is a scholar working on Physical and Theoretical Chemistry, Artificial Intelligence and Spectroscopy, having authored 19 papers that have together received 336 indexed citations. Recurring topics across this work include Neural Networks and Applications (9 papers), Molecular spectroscopy and chirality (3 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Health Informatics (7 citations), Artificial Intelligence (109 citations) and Computer Vision and Pattern Recognition (47 citations). Barry L. Kalman has collaborated with scholars based in United States. Frequent co-authors include Stan C. Kwasny, James W. Richardson, Douglas F. Covey, William R. Reinus, James A. Ferrendelli, William E. Klunk, Anthony Wilson, Andrew F. Laine, Denise D. Beusen and Peter J. McCann. Their work appears in journals such as The Journal of Chemical Physics, Biochemistry and Molecular Pharmacology.
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.