Le Song

About

Le Song is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Le Song has authored 78 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 11 papers in Signal Processing. Recurrent topics in Le Song’s work include Gaussian Processes and Bayesian Inference (10 papers), Advanced Neural Network Applications (10 papers) and Neural Networks and Applications (10 papers). Le Song is often cited by papers focused on Gaussian Processes and Bayesian Inference (10 papers), Advanced Neural Network Applications (10 papers) and Neural Networks and Applications (10 papers). Le Song collaborates with scholars based in United States, China and Australia. Le Song's co-authors include Zhiding Yu, Weiyang Liu, Bhiksha Raj, Yandong Wen, Ming Li, Arthur Gretton, Alex Smola, Kenji Fukumizu, Hanjun Dai and Karsten Borgwardt and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Acta Materialia and Sensors.

In The Last Decade

Co-authorship network of co-authors of Le Song i

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Fields of papers citing papers by Le Song

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Le Song

Since Specialization

Citations

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