Katharina Kann

44 papers and 395 indexed citations i.

About

Katharina Kann is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology. According to data from OpenAlex, Katharina Kann has authored 44 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 2 papers in Experimental and Cognitive Psychology. Recurrent topics in Katharina Kann’s work include Natural Language Processing Techniques (41 papers), Topic Modeling (37 papers) and Multimodal Machine Learning Applications (8 papers). Katharina Kann is often cited by papers focused on Natural Language Processing Techniques (41 papers), Topic Modeling (37 papers) and Multimodal Machine Learning Applications (8 papers). Katharina Kann collaborates with scholars based in United States, Germany and Uruguay. Katharina Kann's co-authors include Hinrich Schütze, Ryan Cotterell, Samuel R. Bowman, Manuel Mager, Kyunghyun Cho, Sascha Rothe, Katja Filippova, Iván Meza, Özlem Çetinoğlu and Alex Warstadt and has published in prestigious journals such as Frontiers in Artificial Intelligence, Open Acess LMU (Ludwig-Maximilians-Universität München) and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Co-authorship network of co-authors of Katharina Kann i

Fields of papers citing papers by Katharina Kann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Katharina Kann

Since Specialization
Citations

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