Daniel Hsu

83 papers and 3.7k indexed citations i.

About

Daniel Hsu is a scholar working on Artificial Intelligence, Statistics and Probability and Computational Mechanics. According to data from OpenAlex, Daniel Hsu has authored 83 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Artificial Intelligence, 19 papers in Statistics and Probability and 16 papers in Computational Mechanics. Recurrent topics in Daniel Hsu’s work include Machine Learning and Algorithms (22 papers), Statistical Methods and Inference (16 papers) and Sparse and Compressive Sensing Techniques (14 papers). Daniel Hsu is often cited by papers focused on Machine Learning and Algorithms (22 papers), Statistical Methods and Inference (16 papers) and Sparse and Compressive Sensing Techniques (14 papers). Daniel Hsu collaborates with scholars based in United States, United Kingdom and Singapore. Daniel Hsu's co-authors include Sham M. Kakade, Mikhail Belkin, Siyuan Ma, Soumik Mandal, Sanjoy Dasgupta, Animashree Anandkumar, Rong Ge, C. Diorio, Miguel Figueroa and Matus Telgarsky and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Monthly Notices of the Royal Astronomical Society and IEEE Transactions on Information Theory.

In The Last Decade

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

Fields of papers citing papers by Daniel Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Daniel Hsu

Since Specialization
Citations

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