Jean-Yves Audibert

About

Jean-Yves Audibert is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Jean-Yves Audibert has authored 30 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 7 papers in Statistics and Probability. Recurrent topics in Jean-Yves Audibert’s work include Machine Learning and Algorithms (10 papers), Statistical Methods and Inference (7 papers) and Image Retrieval and Classification Techniques (6 papers). Jean-Yves Audibert is often cited by papers focused on Machine Learning and Algorithms (10 papers), Statistical Methods and Inference (7 papers) and Image Retrieval and Classification Techniques (6 papers). Jean-Yves Audibert collaborates with scholars based in France, Germany and United States. Jean-Yves Audibert's co-authors include Jean Ponce, Hui Kong, Csaba Szepesvári, Francis Bach, Rodolphe Jenatton, Matthias Hein, Rémi Munos, Josef Šivic, Mikel Rodríguez and Ivan Laptev and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and The Annals of Statistics.

In The Last Decade

Co-authorship network of co-authors of Jean-Yves Audibert i

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Fields of papers citing papers by Jean-Yves Audibert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Yves Audibert. 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 Jean-Yves Audibert. The network helps show where Jean-Yves Audibert may publish in the future.

Countries citing papers authored by Jean-Yves Audibert

Since Specialization

Citations

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