Péter Gács

2.5k citations
47 papers · 1.1k · h-index 17

Impact in

Papers in

Péter Gács

42 papers receiving 970 citations

Peers

Péter Gács
Comparison fields: 5 of 86
  • Computational Theory and Mathematics 638
  • Statistics and Probability 163
  • Mathematical Physics 159
  • Artificial Intelligence 478
  • Geometry and Topology 55
Replace Roman Smolensky with:
Roman Smolensky United States
Daniel Štefankovič United States
Paul C. Shields United States
Michael Drmota Austria
Gianpiero Cattaneo Italy
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Dmitry Panchenko United States
Ioannis Kontoyiannis United States
John C. Kieffer United States
Guilhem Semerjian France
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Citations per field
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Citations per year

Countries citing papers authored by Péter Gács

Since Specialization
Citations

This map shows the geographic impact of Péter Gács'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 Péter Gács with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Péter Gács more than expected).

Fields of papers citing papers by Péter Gács

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Péter Gács. 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 Péter Gács. The network helps show where Péter Gács may publish in the future.

Co-authors

The 20 scholars most cited alongside Péter Gács, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Péter Gács Line = papers co-authored together Péter Gács links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998273
2 197690
3 198685
4 200264
5 200559
6 200156
7 198951
8 198649
9 199445
10 200135
11 198830
12
On playing “Twenty Questions” with a liar
199229
13 198028
14 198322
15 201020
16 201119
17 197716
18 199312
19 200011
20 197910

About Péter Gács

Péter Gács is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Mathematical Physics, Statistics and Probability and Geometry and Topology, having authored 47 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computability, Logic, AI Algorithms (24 papers), Cellular Automata and Applications (11 papers), Stochastic processes and statistical mechanics (8 papers), Statistical Mechanics and Entropy (5 papers), Benford’s Law and Fraud Detection (4 papers), Quantum Computing Algorithms and Architecture (4 papers), Theoretical and Computational Physics (4 papers) and Mathematical Dynamics and Fractals (4 papers). The work is most often cited by research in Computational Theory and Mathematics (638 citations), Statistics and Probability (163 citations), Mathematical Physics (159 citations), Artificial Intelligence (478 citations) and Geometry and Topology (55 citations). Péter Gács has collaborated with scholars based in United States, Hungary and France. Frequent co-authors include Paul Vitányi, Charles H. Bennett, Wojciech H. Zurek, Ming Li, Rudolf Ahlswede, Anna Gál, John Tromp, John H. Reif, Robert M. Gray and Thomas M. Cover. Their work appears in journals such as The Annals of Probability, IEEE Transactions on Information Theory, Theoretical Computer Science, Journal of Computer and System Sciences and Combinatorics Probability Computing.

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.

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