Daniel Beck

22 papers and 279 indexed citations i.

About

Daniel Beck is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Daniel Beck has authored 22 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Signal Processing. Recurrent topics in Daniel Beck’s work include Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Gaussian Processes and Bayesian Inference (5 papers). Daniel Beck is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Gaussian Processes and Bayesian Inference (5 papers). Daniel Beck collaborates with scholars based in Australia, United Kingdom and Germany. Daniel Beck's co-authors include Trevor Cohn, Gholamreza Haffari, Lucia Specia, Kashif Shah, Karin Verspoor, Timothy Baldwin, Christian Hardmeier, Yuxia Wang, Varvara Logacheva and Fethi Bougares and has published in prestigious journals such as NeuroImage, Journal of Biomedical Informatics and Language Resources and Evaluation.

In The Last Decade

Co-authorship network of co-authors of Daniel Beck i

Fields of papers citing papers by Daniel Beck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Beck

Since Specialization
Citations

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