Lin F. Yang

About

Lin F. Yang is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computational Theory and Mathematics. According to data from OpenAlex, Lin F. Yang has authored 81 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 13 papers in Management Science and Operations Research and 12 papers in Computational Theory and Mathematics. Recurrent topics in Lin F. Yang’s work include Machine Learning and Algorithms (19 papers), Reinforcement Learning in Robotics (13 papers) and Algorithms and Data Compression (10 papers). Lin F. Yang is often cited by papers focused on Machine Learning and Algorithms (19 papers), Reinforcement Learning in Robotics (13 papers) and Algorithms and Data Compression (10 papers). Lin F. Yang collaborates with scholars based in United States, China and United Kingdom. Lin F. Yang's co-authors include Miguel A. Aragón-Calvo, Steve Hanneke, Jaime Carbonell, Wen Jiang, Zhiming Huang, Mark C. Neyrinck, Joseph Silk, Bridget Falck, Mengdi Wang and Athanasios A. Pantelous and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Chemical Communications and Optics Express.

In The Last Decade

Co-authorship network of co-authors of Lin F. Yang i

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Fields of papers citing papers by Lin F. Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lin F. Yang. 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 Lin F. Yang. The network helps show where Lin F. Yang may publish in the future.

Countries citing papers authored by Lin F. Yang

Since Specialization

Citations

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