Jon McAuliffe
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Machine Learning and Algorithms
- Bayesian Methods and Mixture Models
- General Social Sciences top 0.2%
Papers in
-
- Bayesian Methods and Mixture Models 5
- Gaussian Processes and Bayesian Inference 3
- Algorithms and Data Compression 2
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- RNA and protein synthesis mechanisms 5
- Genomics and Phylogenetic Studies 4
- Co-authors
- David M. Blei (3 shared papers)Michael I. Jordan (11 shared papers)Peter L. Bartlett (5 shared papers)Lior Pachter (3 shared papers)Dario Boffelli (1 shared paper)Ivan Ovcharenko (1 shared paper)Dmitriy Ovcharenko (1 shared paper)Edward M. Rubin (1 shared paper)
- Journals
- Journal of the American Statistical Association (3 papers)Proceedings of the National Academy of Sciences (3 papers)Bioinformatics (2 papers)Statistical Science (2 papers)The Annals of Applied Statistics (1 paper)
- Partner nations
- United StatesSwitzerlandAustralia
In The Last Decade
Jon McAuliffe
31 papers receiving 2.8k citations
Jon McAuliffe's Hit Papers
Peers
Comparison fields: 5 of 176
- Artificial Intelligence 1.4k
- General Social Sciences 114
- Statistics and Probability 261
- Computer Vision and Pattern Recognition 408
- Signal Processing 130
Countries citing papers authored by Jon McAuliffe
This map shows the geographic impact of Jon McAuliffe'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 Jon McAuliffe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon McAuliffe more than expected).
Fields of papers citing papers by Jon McAuliffe
This network shows the impact of papers produced by Jon McAuliffe. 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 Jon McAuliffe. The network helps show where Jon McAuliffe may publish in the future.
Co-authors
The 25 scholars most cited alongside Jon McAuliffe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Supervised Topic Models Hit paper breakdown → | 2010 | 956 |
| 2 | Convexity, Classification, and Risk Bounds Hit paper breakdown → | 2006 | 645 |
| 3 | 2003 | 407 | |
| 4 | 2008 | 245 | |
| 5 | 2003 | 149 | |
| 6 | 2010 | 96 | |
| 7 | 2005 | 86 | |
| 8 | 2006 | 86 | |
| 9 | 2023 | 51 | |
| 10 | 2004 | 39 | |
| 11 | 2005 | 34 | |
| 12 | Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates | 2003 | 30 |
| 13 | 2010 | 20 | |
| 14 | 2020 | 19 | |
| 15 | 2002 | 16 | |
| 16 | 2005 | 13 | |
| 17 | 2003 | 13 | |
| 18 | 2014 | 12 | |
| 19 | 2018 | 11 | |
| 20 | 2019 | 9 |
About Jon McAuliffe
Jon McAuliffe is a scholar working on Artificial Intelligence, Molecular Biology, Statistics and Probability, Genetics and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 3.0k indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), RNA and protein synthesis mechanisms (5 papers), Bayesian Methods and Mixture Models (5 papers), Genomics and Phylogenetic Studies (4 papers), Galaxies: Formation, Evolution, Phenomena (3 papers), Gaussian Processes and Bayesian Inference (3 papers), Advanced Statistical Methods and Models (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), General Social Sciences (114 citations), Statistics and Probability (261 citations), Computer Vision and Pattern Recognition (408 citations) and Signal Processing (130 citations). Jon McAuliffe has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include David M. Blei, Michael I. Jordan, Peter L. Bartlett, Lior Pachter, Dario Boffelli, Ivan Ovcharenko, Dmitriy Ovcharenko, Edward M. Rubin, Michael Braun and Oleg Paliy. Their work appears in journals such as Journal of the American Statistical Association, Proceedings of the National Academy of Sciences, Bioinformatics, Statistical Science and The Annals of Applied Statistics.
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.