John Winn
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Image and Video Retrieval Techniques 18
- Advanced Vision and Imaging 9
- Image Retrieval and Classification Techniques 7
- Advanced Neural Network Applications 6
- Media Technology top 0.1%
- Artificial Intelligence top 0.05%
- Bayesian Modeling and Causal Inference 8
- Machine Learning and Algorithms 7
- Gaussian Processes and Bayesian Inference 7
- Aerospace Engineering top 0.2%
- Robotics and Sensor-Based Localization 6
- Co-authors
- Christopher K. I. WilliamsAndrew ZissermanLuc Van GoolMark EveringhamS. M. Ali EslamiChris BishopAntonio CriminisiIain Buchan
- Journals
- International Journal of Computer Vision (4 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Bioinformatics (2 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
John Winn
57 papers receiving 21.5k citations
Hit Papers
Peers
Comparison fields: 5 of 216
- Computer Vision and Pattern Recognition 15.4k
- Media Technology 2.1k
- Artificial Intelligence 6.1k
- Industrial and Manufacturing Engineering 989
- Aerospace Engineering 2.0k
Countries citing papers authored by John Winn
This map shows the geographic impact of John Winn'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 Winn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Winn more than expected).
Fields of papers citing papers by John Winn
This network shows the impact of papers produced by John Winn. 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 Winn. The network helps show where John Winn may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John Winn, 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 | 1 | |
| 2 | Enterprise Alexandria: Online High-Precision Enterprise Knowledge Base Construction with Typed Entities | 2021 | 1 |
| 3 | Alexandria: Unsupervised High-Precision Knowledge Base Construction using a Probabilistic Program | 2019 | 5 |
| 4 | 2015 | 7 | |
| 5 | Just-In-Time Learning for Fast and Flexible Inference | 2014 | 4 |
| 6 | Structural Expectation Propagation (SEP): Bayesian Structure Learning for Networks with Latent Variables | 2013 | 4 |
| 7 | Decision Jungles: Compact and Rich Models for Classification | 2013 | 58 |
| 8 | Learning to Pass Expectation Propagation Messages | 2013 | 7 |
| 9 | Causality with Gates | 2012 | 3 |
| 10 | Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analysesbreakdown → | 2012 | 486 |
| 11 | 2010 | 311 | |
| 12 | 2010 | 39 | |
| 13 | 2010 | 273 | |
| 14 | The Pascal Visual Object Classes (VOC) Challengebreakdown → | 2009 | 12010 |
| 15 | 2009 | 33 | |
| 16 | A Unified Modeling Approach to Data-Intensive Healthcare | 2009 | 20 |
| 17 | 2008 | 17 | |
| 18 | Variational Message Passingbreakdown → | 2005 | 415 |
| 19 | Structured Variational Distributions in VIBES | 2003 | 23 |
| 20 | VIBES: A Variational Inference Engine for Bayesian Networks | 2002 | 57 |
About John Winn
John Winn is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aging, having authored 59 papers that have together received 22.2k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (18 papers), Advanced Vision and Imaging (9 papers), Bayesian Modeling and Causal Inference (8 papers), Machine Learning and Algorithms (7 papers), Image Retrieval and Classification Techniques (7 papers), Gaussian Processes and Bayesian Inference (7 papers), Advanced Neural Network Applications (6 papers) and Robotics and Sensor-Based Localization (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (15.4k citations), Media Technology (2.1k citations) and Artificial Intelligence (6.1k citations). John Winn has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Christopher K. I. Williams, Andrew Zisserman, Luc Van Gool, Mark Everingham, S. M. Ali Eslami, Chris Bishop, Antonio Criminisi, Iain Buchan, Jamie Shotton and Carsten Rother. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, Bioinformatics, ACM Transactions on Graphics and American Journal of Respiratory and Critical Care Medicine.
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.