A. K. Rigler
Impact in
- Artificial Intelligence top 5%
- Neural Networks and Applications
- Machine Learning and ELM
- Fuzzy Logic and Control Systems
- Metaheuristic Optimization Algorithms Research
- Neural Networks and Reservoir Computing
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in
-
- Photorefractive and Nonlinear Optics 3
- Adaptive optics and wavefront sensing 3
- Digital Holography and Microscopy 2
-
- Neural Networks and Applications 4
- Co-authors
- Thomas P. Vogl (7 shared papers)Daniel L. Alkon (2 shared papers)John M. Irvine (1 shared paper)Kim T. Blackwell (1 shared paper)G. B. Brandt (2 shared papers)Richard S. Varga (1 shared paper)
- Journals
- Biological Cybernetics (2 papers)Journal of Computational Physics (1 paper)Physics Letters A (1 paper)Journal of Optimization Theory and Applications (1 paper)Neural Networks (1 paper)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
A. K. Rigler
18 papers receiving 948 citations
A. K. Rigler's Hit Papers
Peers
Comparison fields: 5 of 121
- Artificial Intelligence 458
- Signal Processing 120
- Computer Vision and Pattern Recognition 158
- Control and Systems Engineering 156
- Numerical Analysis 31
Countries citing papers authored by A. K. Rigler
This map shows the geographic impact of A. K. Rigler'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 A. K. Rigler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. K. Rigler more than expected).
Fields of papers citing papers by A. K. Rigler
This network shows the impact of papers produced by A. K. Rigler. 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 A. K. Rigler. The network helps show where A. K. Rigler may publish in the future.
Co-authors
The 6 scholars most cited alongside A. K. Rigler, 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 | Accelerating the convergence of the back-propagation method Hit paper breakdown → | 1988 | 810 |
| 2 | 1991 | 72 | |
| 3 | 1990 | 36 | |
| 4 | 1965 | 16 | |
| 5 | 1971 | 14 | |
| 6 | 1965 | 10 | |
| 7 | 1989 | 9 | |
| 8 | 1982 | 9 | |
| 9 | 1971 | 9 | |
| 10 | 1966 | 6 | |
| 11 | 1967 | 5 | |
| 12 | 1967 | 5 | |
| 13 | 1973 | 5 | |
| 14 | 1992 | 4 | |
| 15 | 1970 | 2 | |
| 16 | 1968 | 2 | |
| 17 | 1972 | 2 | |
| 18 | 1979 | 1 | |
| 19 | 1969 | 1 |
About A. K. Rigler
A. K. Rigler is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Computational Theory and Mathematics, Numerical Analysis and Computational Mechanics, having authored 19 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Photonic and Optical Devices (3 papers), Photorefractive and Nonlinear Optics (3 papers), Advanced optical system design (3 papers), Adaptive optics and wavefront sensing (3 papers), Advanced Optimization Algorithms Research (2 papers), Digital Holography and Microscopy (2 papers) and Matrix Theory and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (458 citations), Signal Processing (120 citations), Computer Vision and Pattern Recognition (158 citations), Control and Systems Engineering (156 citations) and Numerical Analysis (31 citations). A. K. Rigler has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Thomas P. Vogl, Daniel L. Alkon, John M. Irvine, Kim T. Blackwell, G. B. Brandt and Richard S. Varga. Their work appears in journals such as Biological Cybernetics, Journal of Computational Physics, Physics Letters A, Journal of Optimization Theory and Applications and Neural Networks.
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.