Tomas Hrycej

About

Tomas Hrycej is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Tomas Hrycej has authored 16 papers receiving a total of 135 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Statistics and Probability. Recurrent topics in Tomas Hrycej’s work include Neural Networks and Applications (3 papers), Financial Risk and Volatility Modeling (2 papers) and Multimodal Machine Learning Applications (1 paper). Tomas Hrycej is often cited by papers focused on Neural Networks and Applications (3 papers), Financial Risk and Volatility Modeling (2 papers) and Multimodal Machine Learning Applications (1 paper). Tomas Hrycej collaborates with scholars based in Germany, Switzerland and United Kingdom. Tomas Hrycej's co-authors include Rafael Schmidt, M. Grabert, Jochen Hipp and Siegfried Handschuh and has published in prestigious journals such as Artificial Intelligence, Neurocomputing and Computational Statistics & Data Analysis.

In The Last Decade

Co-authorship network of co-authors of Tomas Hrycej i

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Fields of papers citing papers by Tomas Hrycej

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Tomas Hrycej

Since Specialization

Citations

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