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
-
- Statistical Methods and Inference 6
- Virology 2
- HIV Research and Treatment 2
- Co-authors
- David M. BleiMichael I. JordanPeter L. BartlettLior PachterIvan OvcharenkoEdward M. RubinDario BoffelliDmitriy Ovcharenko
- 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)Journal of Bacteriology (1 paper)
- Partner nations
- United StatesAustraliaDenmark
In The Last Decade
Jon McAuliffe
31 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Artificial Intelligence 1.3k
- General Social Sciences 107
- Statistics and Probability 247
- Computer Vision and Pattern Recognition 365
- Signal Processing 121
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 46 | |
| 2 | 2020 | 17 | |
| 3 | Rao-Blackwellized Stochastic Gradients for Discrete Distributions | 2019 | 3 |
| 4 | 2019 | 7 | |
| 5 | Uniform, nonparametric, non-asymptotic confidence sequences | 2018 | 3 |
| 6 | 2018 | 9 | |
| 7 | A Gaussian process model of quasar spectral energy distributions | 2015 | 1 |
| 8 | 2014 | 12 | |
| 9 | 2010 | 20 | |
| 10 | 2008 | 224 | |
| 11 | A spatially varying two-sample recombinant coalescent, with applications to HIV escape response. | 2008 | 5 |
| 12 | 2006 | 1 | |
| 13 | 2006 | 80 | |
| 14 | Convexity, Classification, and Risk Bounds Hit paper breakdown → | 2006 | 596 |
| 15 | 2005 | 13 | |
| 16 | 2004 | 5 | |
| 17 | 2003 | 397 | |
| 18 | Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates | 2003 | 26 |
| 19 | 2003 | 140 | |
| 20 | Data compression of the exercise ECG using a Kohonen neural network. | 1993 | 2 |
About Jon McAuliffe
Jon McAuliffe is a scholar working on Statistics and Probability, Virology, Artificial Intelligence, General Social Sciences and Hardware and Architecture, having authored 31 papers that have together received 2.7k indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), Bayesian Methods and Mixture Models (5 papers), RNA and protein synthesis mechanisms (5 papers), Genomics and Phylogenetic Studies (4 papers), Galaxies: Formation, Evolution, Phenomena (3 papers), Gaussian Processes and Bayesian Inference (3 papers), Sparse and Compressive Sensing Techniques (2 papers) and HIV Research and Treatment (2 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), General Social Sciences (107 citations), Statistics and Probability (247 citations), Computer Vision and Pattern Recognition (365 citations) and Signal Processing (121 citations). Jon McAuliffe has collaborated with scholars based in United States, Australia and Denmark. Frequent co-authors include David M. Blei, Michael I. Jordan, Peter L. Bartlett, Lior Pachter, Ivan Ovcharenko, Edward M. Rubin, Dario Boffelli, Dmitriy Ovcharenko, 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 Journal of Bacteriology.
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.