David Grangier

41 papers and 5.3k indexed citations i.

About

David Grangier is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, David Grangier has authored 41 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 9 papers in Signal Processing. Recurrent topics in David Grangier’s work include Natural Language Processing Techniques (25 papers), Topic Modeling (24 papers) and Multimodal Machine Learning Applications (11 papers). David Grangier is often cited by papers focused on Natural Language Processing Techniques (25 papers), Topic Modeling (24 papers) and Multimodal Machine Learning Applications (11 papers). David Grangier collaborates with scholars based in United States, Switzerland and Israel. David Grangier's co-authors include Michael Auli, Myle Ott, Sergey Edunov, Yann Dauphin, Angela Fan, Dario Pavllo, Jonas Gehring, Christoph Feichtenhofer, Sam Gross and Nathan Ng and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Speech Communication.

In The Last Decade

Co-authorship network of co-authors of David Grangier i

Fields of papers citing papers by David Grangier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by David Grangier

Since Specialization
Citations

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