John Lafferty
Impact in
- Artificial Intelligence top 0.01%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
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- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
Papers in
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- Topic Modeling 28
- Natural Language Processing Techniques 23
- Bayesian Methods and Mixture Models 18
- Neural Networks and Applications 16
- Bayesian Modeling and Causal Inference 15
- Machine Learning and Algorithms 15
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- Statistical Methods and Inference 19
- Co-authors
- Andrew McCallum (3 shared papers)Fernando C. N. Pereira (1 shared paper)ChengXiang Zhai (11 shared papers)David M. Blei (7 shared papers)Xiaojin Zhu (11 shared papers)Zoubin Ghahramani (5 shared papers)Adam L. Berger (9 shared papers)Risi Kondor (1 shared paper)
- Journals
- American Journal of Clinical Pathology (9 papers)ACM SIGIR Forum (6 papers)Transactions of the American Mathematical Society (4 papers)Archives of Pathology & Laboratory Medicine (3 papers)Proceedings of the National Academy of Sciences (3 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
John Lafferty
172 papers receiving 28.2k citations
John Lafferty's Hit Papers
Peers
Comparison fields: 5 of 217
- Artificial Intelligence 20.4k
- Computer Vision and Pattern Recognition 6.9k
- Information Systems 6.3k
- General Social Sciences 710
- Signal Processing 2.4k
Countries citing papers authored by John Lafferty
This map shows the geographic impact of John Lafferty'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 John Lafferty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Lafferty more than expected).
Fields of papers citing papers by John Lafferty
This network shows the impact of papers produced by John Lafferty. 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 John Lafferty. The network helps show where John Lafferty may publish in the future.
Co-authors
The 25 scholars most cited alongside John Lafferty, 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 176 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data Hit paper breakdown → | 2001 | 9694 |
| 2 | Semi-supervised learning using Gaussian fields and harmonic functions Hit paper breakdown → | 2003 | 2639 |
| 3 | Dynamic topic models Hit paper breakdown → | 2006 | 1729 |
| 4 | A statistical approach to machine translation Hit paper breakdown → | 1990 | 1156 |
| 5 | A study of smoothing methods for language models applied to information retrieval Hit paper breakdown → | 2004 | 940 |
| 6 | Inducing features of random fields Hit paper breakdown → | 1997 | 793 |
| 7 | A study of smoothing methods for language models applied to Ad Hoc information retrieval Hit paper breakdown → | 2001 | 785 |
| 8 | Correlated Topic Models Hit paper breakdown → | 2005 | 660 |
| 9 | Using Maximum Entropy for Text Classification | 1999 | 600 |
| 10 | Model-based feedback in the language modeling approach to information retrieval Hit paper breakdown → | 2001 | 596 |
| 11 | Diffusion Kernels on Graphs and Other Discrete Input Spaces Hit paper breakdown → | 2002 | 563 |
| 12 | 1999 | 513 | |
| 13 | Semi-supervised learning with graphs Hit paper breakdown → | 2005 | 469 |
| 14 | 2001 | 459 | |
| 15 | A correlated topic model of Science Hit paper breakdown → | 2018 | 416 |
| 16 | Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions | 2003 | 365 |
| 17 | 2004 | 347 | |
| 18 | 2009 | 334 | |
| 19 | 1999 | 327 | |
| 20 | 2003 | 321 |
About John Lafferty
John Lafferty is a scholar working on Artificial Intelligence, Statistics and Probability, Genetics, Information Systems and Signal Processing, having authored 176 papers that have together received 30.6k indexed citations. Recurring topics across this work include Topic Modeling (28 papers), Natural Language Processing Techniques (23 papers), Statistical Methods and Inference (19 papers), Bayesian Methods and Mixture Models (18 papers), Hemoglobinopathies and Related Disorders (17 papers), Neural Networks and Applications (16 papers), Bayesian Modeling and Causal Inference (15 papers) and Machine Learning and Algorithms (15 papers). The work is most often cited by research in Artificial Intelligence (20.4k citations), Computer Vision and Pattern Recognition (6.9k citations), Information Systems (6.3k citations), General Social Sciences (710 citations) and Signal Processing (2.4k citations). John Lafferty has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Andrew McCallum, Fernando C. N. Pereira, ChengXiang Zhai, David M. Blei, Xiaojin Zhu, Zoubin Ghahramani, Adam L. Berger, Risi Kondor, S. Della Pietra and V. Della Pietra. Their work appears in journals such as American Journal of Clinical Pathology, ACM SIGIR Forum, Transactions of the American Mathematical Society, Archives of Pathology & Laboratory Medicine and Proceedings of the National Academy of Sciences.
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.