Mark Huber

37 papers and 415 indexed citations i.

About

Mark Huber is a scholar working on Statistics and Probability, Artificial Intelligence and Mathematical Physics. According to data from OpenAlex, Mark Huber has authored 37 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Statistics and Probability, 19 papers in Artificial Intelligence and 12 papers in Mathematical Physics. Recurrent topics in Mark Huber’s work include Markov Chains and Monte Carlo Methods (26 papers), Bayesian Methods and Mixture Models (12 papers) and Stochastic processes and statistical mechanics (12 papers). Mark Huber is often cited by papers focused on Markov Chains and Monte Carlo Methods (26 papers), Bayesian Methods and Mixture Models (12 papers) and Stochastic processes and statistical mechanics (12 papers). Mark Huber collaborates with scholars based in United States and Denmark. Mark Huber's co-authors include Dawn B. Woodard, Scott C. Schmidler, Robert L. Wolpert, James Allen Fill, Joshua E. S. Socolar, David G. Schaeffer, Brian P. Tighe, Jesper Møller, Adrian Dobra and Yuguo Chen and has published in prestigious journals such as Biometrics, Systematic Biology and American Mathematical Monthly.

In The Last Decade

Co-authorship network of co-authors of Mark Huber i

Fields of papers citing papers by Mark Huber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Mark Huber

Since Specialization
Citations

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