Dmitry Krotov
Impact in
- Nuclear and High Energy Physics top 10%
- Black Holes and Theoretical Physics
- Astronomy and Astrophysics top 10%
- Cosmology and Gravitation Theories
Papers in
-
- Black Holes and Theoretical Physics 5
- Particle physics theoretical and experimental studies 2
- Co-authors
- A. M. Polyakov (1 shared paper)J. J. Hopfield (1 shared paper)Julien Dubuis (1 shared paper)Thomas Gregor (1 shared paper)William Bialek (1 shared paper)Ksenia V. Kastanenka (1 shared paper)В. И. Захаров (1 shared paper)Валерий Анатольевич Рубаков (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (4 papers)Nuclear Physics B (2 papers)Journal of Computational Physics (1 paper)Frontiers in Big Data (1 paper)Nature Reviews Physics (1 paper)
- Partner nations
- United StatesRussiaGermany
In The Last Decade
Dmitry Krotov
12 papers receiving 378 citations
Peers
Comparison fields: 5 of 75
- Nuclear and High Energy Physics 113
- Astronomy and Astrophysics 123
- Cognitive Neuroscience 80
- Statistical and Nonlinear Physics 53
- Artificial Intelligence 76
Countries citing papers authored by Dmitry Krotov
This map shows the geographic impact of Dmitry Krotov'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 Dmitry Krotov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry Krotov more than expected).
Fields of papers citing papers by Dmitry Krotov
This network shows the impact of papers produced by Dmitry Krotov. 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 Dmitry Krotov. The network helps show where Dmitry Krotov may publish in the future.
Co-authors
The 19 scholars most cited alongside Dmitry Krotov, 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 | 2011 | 99 | |
| 2 | 2014 | 88 | |
| 3 | 2019 | 84 | |
| 4 | 2023 | 38 | |
| 5 | 2005 | 27 | |
| 6 | 2023 | 26 | |
| 7 | 2008 | 9 | |
| 8 | 2025 | 6 | |
| 9 | 2024 | 4 | |
| 10 | 2005 | 3 | |
| 11 | 2025 | 3 | |
| 12 | 2007 | 1 | |
| 13 | 2022 | 0 |
About Dmitry Krotov
Dmitry Krotov is a scholar working on Nuclear and High Energy Physics, Statistical and Nonlinear Physics, Cognitive Neuroscience, Artificial Intelligence and Electrical and Electronic Engineering, having authored 13 papers that have together received 388 indexed citations. Recurring topics across this work include Black Holes and Theoretical Physics (5 papers), Neural dynamics and brain function (4 papers), Neural Networks and Applications (3 papers), Advanced Memory and Neural Computing (3 papers), Cosmology and Gravitation Theories (3 papers), Particle physics theoretical and experimental studies (2 papers), Bioinformatics and Genomic Networks (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (113 citations), Astronomy and Astrophysics (123 citations), Cognitive Neuroscience (80 citations), Statistical and Nonlinear Physics (53 citations) and Artificial Intelligence (76 citations). Dmitry Krotov has collaborated with scholars based in United States, Russia and Germany. Frequent co-authors include A. M. Polyakov, J. J. Hopfield, Julien Dubuis, Thomas Gregor, William Bialek, Ksenia V. Kastanenka, В. И. Захаров, Валерий Анатольевич Рубаков, C. Rebbi and A. Losev. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nuclear Physics B, Journal of Computational Physics, Frontiers in Big Data and Nature Reviews Physics.
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.