Balázs Kégl

30 papers and 1.5k indexed citations i.

About

Balázs Kégl is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Balázs Kégl has authored 30 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 6 papers in Signal Processing. Recurrent topics in Balázs Kégl’s work include Music and Audio Processing (4 papers), Speech and Audio Processing (4 papers) and Markov Chains and Monte Carlo Methods (3 papers). Balázs Kégl is often cited by papers focused on Music and Audio Processing (4 papers), Speech and Audio Processing (4 papers) and Markov Chains and Monte Carlo Methods (3 papers). Balázs Kégl collaborates with scholars based in France, Canada and Hungary. Balázs Kégl's co-authors include Adam Krzyżak, Tamás Linder, K. Zeger, Róbert Busa‐Fekete, Gaël Varoquaux, Norman Casagrande, Douglas Eck, James Bergstra, Dumitru Erhan and Réka Spohn and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition.

In The Last Decade

Co-authorship network of co-authors of Balázs Kégl i

Fields of papers citing papers by Balázs Kégl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Balázs Kégl

Since Specialization
Citations

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

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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