Geoff Pleiss

14 papers and 1.1k indexed citations i.

About

Geoff Pleiss is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability. According to data from OpenAlex, Geoff Pleiss has authored 14 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Statistics and Probability. Recurrent topics in Geoff Pleiss’s work include Gaussian Processes and Bayesian Inference (6 papers), Machine Learning and Data Classification (5 papers) and Neural Networks and Applications (3 papers). Geoff Pleiss is often cited by papers focused on Gaussian Processes and Bayesian Inference (6 papers), Machine Learning and Data Classification (5 papers) and Neural Networks and Applications (3 papers). Geoff Pleiss collaborates with scholars based in United States, China and Canada. Geoff Pleiss's co-authors include Kilian Q. Weinberger, Yu Sun, Chuan Guo, Gao Huang, Zhuang Liu, Laurens van der Maaten, Jacob R. Gardner, Kavita Bala, Paul Upchurch and Robert Pless and has published in prestigious journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Hydrometeorology.

In The Last Decade

Co-authorship network of co-authors of Geoff Pleiss i

Fields of papers citing papers by Geoff Pleiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Geoff Pleiss

Since Specialization
Citations

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