Charles Sutton
Impact in
- Artificial Intelligence top 0.2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Software top 1%
Papers in
-
- Natural Language Processing Techniques 26
- Topic Modeling 25
- Bayesian Modeling and Causal Inference 9
- Gaussian Processes and Bayesian Inference 8
- Bayesian Methods and Mixture Models 8
- Machine Learning and Data Classification 7
-
- Software Engineering Research 16
- Co-authors
- Akash Srivastava (8 shared papers)Nigel Goddard (5 shared papers)Mingjun Zhong (5 shared papers)Andrew McCallum (17 shared papers)Khashayar Rohanimanesh (3 shared papers)Miltiadis Allamanis (8 shared papers)Chaoyun Zhang (1 shared paper)Michael I. Jordan (7 shared papers)
- Journals
- IEEE Transactions on Software Engineering (2 papers)Proceedings of the VLDB Endowment (2 papers)Cancer (1 paper)Journal of Machine Learning Research (1 paper)ACM Transactions on Modeling and Computer Simulation (1 paper)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Charles Sutton
96 papers receiving 6.6k citations
Charles Sutton's Hit Papers
Peers
Comparison fields: 5 of 187
- Artificial Intelligence 3.5k
- Software 343
- Computer Vision and Pattern Recognition 1.5k
- Signal Processing 690
- Information Systems 1.4k
Countries citing papers authored by Charles Sutton
This map shows the geographic impact of Charles Sutton'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 Charles Sutton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charles Sutton more than expected).
Fields of papers citing papers by Charles Sutton
This network shows the impact of papers produced by Charles Sutton. 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 Charles Sutton. The network helps show where Charles Sutton may publish in the future.
Co-authors
The 25 scholars most cited alongside Charles Sutton, 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 97 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Proceedings for the 5th International Conference on Learning Representations Hit paper breakdown → | 2017 | 1374 |
| 2 | Advances in Neural Information Processing Systems 27 (NIPS 2014) Hit paper breakdown → | 2014 | 1337 |
| 3 | 2004 | 446 | |
| 4 | Sequence-to-Point Learning With Neural Networks for Non-Intrusive Load Monitoring Hit paper breakdown → | 2018 | 363 |
| 5 | An Introduction to Conditional Random Fields Hit paper breakdown → | 2012 | 324 |
| 6 | Suggesting accurate method and class names Hit paper breakdown → | 2015 | 234 |
| 7 | 2006 | 216 | |
| 8 | 2007 | 201 | |
| 9 | 2013 | 178 | |
| 10 | Exploiting machine learning to subvert your spam filter | 2008 | 174 |
| 11 | 2019 | 164 | |
| 12 | Statistical machine learning makes automatic control practical for internet datacenters | 2009 | 143 |
| 13 | 2007 | 108 | |
| 14 | 2013 | 106 | |
| 15 | Collective Segmentation and Labeling of Distant Entities in Information Extraction | 2004 | 102 |
| 16 | VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning | 2017 | 97 |
| 17 | 4th Biennial Conference on Innovative Data Systems Research (CIDR) | 2009 | 85 |
| 18 | 2009 | 83 | |
| 19 | 2017 | 74 | |
| 20 | Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010 | 2010 | 72 |
About Charles Sutton
Charles Sutton is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Signal Processing and Software, having authored 97 papers that have together received 6.9k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (26 papers), Topic Modeling (25 papers), Software Engineering Research (16 papers), Bayesian Modeling and Causal Inference (9 papers), Gaussian Processes and Bayesian Inference (8 papers), Bayesian Methods and Mixture Models (8 papers), Machine Learning and Data Classification (7 papers) and Software Testing and Debugging Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (3.5k citations), Software (343 citations), Computer Vision and Pattern Recognition (1.5k citations), Signal Processing (690 citations) and Information Systems (1.4k citations). Charles Sutton has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Akash Srivastava, Nigel Goddard, Mingjun Zhong, Andrew McCallum, Khashayar Rohanimanesh, Miltiadis Allamanis, Chaoyun Zhang, Michael I. Jordan, Earl T. Barr and Christian Bird. Their work appears in journals such as IEEE Transactions on Software Engineering, Proceedings of the VLDB Endowment, Cancer, Journal of Machine Learning Research and ACM Transactions on Modeling and Computer Simulation.
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.