Tamás Geszti
- Artificial Intelligence top 10%
- Atomic and Molecular Physics, and Optics
- Materials Chemistry
- Condensed Matter Physics
- Statistical and Nonlinear Physics top 10%
- Co-authors
- István CsabaiIstván LadungaLajos DiósiFerenc PázmándiImre DerényiG. GyörgyiAndrás BodorGábor Vattay
- Topics
- Neural Networks and Applications (10 papers)Advanced Thermodynamics and Statistical Mechanics (7 papers)Quantum Information and Cryptography (6 papers)
In The Last Decade
Tamás Geszti
32 papers receiving 314 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 127
- Atomic and Molecular Physics, and Optics 125
- Materials Chemistry 105
- Condensed Matter Physics 58
- Statistical and Nonlinear Physics 48
Countries citing papers authored by Tamás Geszti
This map shows the geographic impact of Tamás Geszti'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 Tamás Geszti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tamás Geszti more than expected).
Fields of papers citing papers by Tamás Geszti
This network shows the impact of papers produced by Tamás Geszti. 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 Tamás Geszti. The network helps show where Tamás Geszti may publish in the future.
Co-authorship network of co-authors of Tamás Geszti
This figure shows the co-authorship network connecting the top 25 collaborators of Tamás Geszti. A scholar is included among the top collaborators of Tamás Geszti 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 Tamás Geszti. Tamás Geszti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Multilocal-realistic nonlinear dynamics of quantum collapse | 0 |
| 2 | 31 | |
| 3 | 17 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 6 | |
| 7 | Habituation in Learning Vector Quantization. | 3 |
| 8 | 4 | |
| 9 | 34 | |
| 10 | 50 | |
| 11 | 1 | |
| 12 | 7 | |
| 13 | 1 | |
| 14 | 7 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 2 | |
| 20 | 9 |
About Tamás Geszti
Tamás Geszti is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Atomic and Molecular Physics, and Optics, having authored 34 papers that have together received 336 indexed citations. Recurring topics across this work include Neural Networks and Applications (10 papers), Advanced Thermodynamics and Statistical Mechanics (7 papers) and Quantum Information and Cryptography (6 papers). The work is most often cited by research in Condensed Matter Physics (58 citations), Atomic and Molecular Physics, and Optics (125 citations) and Ceramics and Composites (23 citations). Tamás Geszti has collaborated with scholars based in Hungary, Germany and Belgium. Frequent co-authors include István Csabai, István Ladunga, Lajos Diósi, Ferenc Pázmándi, Imre Derényi, G. Györgyi, András Bodor, Gábor Vattay, Wolfram Schommers and Dezső L. Beke. Their work appears in journals such as Physical Review Letters, The Journal of Chemical Physics and Physical review. B, Condensed matter.
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.