Jesse Davis
Impact in
- Artificial Intelligence top 0.5%
- Anomaly Detection Techniques and Applications
- Bayesian Modeling and Causal Inference
- Imbalanced Data Classification Techniques
- Topic Modeling
- Machine Learning and Data Classification
- Signal Processing top 1%
Papers in
-
- Bayesian Modeling and Causal Inference 41
- Anomaly Detection Techniques and Applications 26
- Machine Learning and Algorithms 17
- Topic Modeling 16
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- Sports Analytics and Performance 29
- Co-authors
- Mark Goadrich (1 shared paper)Pedro Domingos (4 shared papers)Wannes Meert (28 shared papers)Jan Van Haaren (21 shared papers)Tom Decroos (12 shared papers)Guy Van den Broeck (9 shared papers)Vı́tor Santos Costa (11 shared papers)Nima Taghipour (8 shared papers)
- Journals
- Machine Learning (6 papers)Frontiers in Bioengineering and Biotechnology (4 papers)Sensors (4 papers)Lecture notes in computer science (27 papers)Data Mining and Knowledge Discovery (3 papers)
- Partner nations
- BelgiumUnited StatesUnited Kingdom
In The Last Decade
Jesse Davis
180 papers receiving 6.7k citations
Jesse Davis's Hit Papers
Peers
Comparison fields: 5 of 204
- Artificial Intelligence 3.1k
- Signal Processing 586
- Orthopedics and Sports Medicine 358
- Computer Vision and Pattern Recognition 938
- Health Information Management 138
Countries citing papers authored by Jesse Davis
This map shows the geographic impact of Jesse Davis'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 Jesse Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesse Davis more than expected).
Fields of papers citing papers by Jesse Davis
This network shows the impact of papers produced by Jesse Davis. 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 Jesse Davis. The network helps show where Jesse Davis may publish in the future.
Co-authors
The 25 scholars most cited alongside Jesse Davis, 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 196 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The relationship between Precision-Recall and ROC curves Hit paper breakdown → | 2006 | 4366 |
| 2 | 2009 | 166 | |
| 3 | Learning First-Order Horn Clauses from Web Text | 2010 | 134 |
| 4 | 2011 | 107 | |
| 5 | 1983 | 107 | |
| 6 | 2018 | 83 | |
| 7 | 2009 | 73 | |
| 8 | 2017 | 58 | |
| 9 | 2018 | 57 | |
| 10 | 2020 | 56 | |
| 11 | 2018 | 54 | |
| 12 | 2015 | 52 | |
| 13 | 2010 | 48 | |
| 14 | Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation. | 2012 | 47 |
| 15 | 2018 | 43 | |
| 16 | 2005 | 42 | |
| 17 | 1986 | 41 | |
| 18 | 2015 | 39 | |
| 19 | 2013 | 39 | |
| 20 | View learning for statistical relational learning: with an application to mammography | 2005 | 38 |
About Jesse Davis
Jesse Davis is a scholar working on Artificial Intelligence, Economics and Econometrics, Orthopedics and Sports Medicine, Signal Processing and Information Systems, having authored 196 papers that have together received 7.0k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (41 papers), Sports Analytics and Performance (29 papers), Sports Performance and Training (26 papers), Anomaly Detection Techniques and Applications (26 papers), Time Series Analysis and Forecasting (20 papers), Data Mining Algorithms and Applications (18 papers), Machine Learning and Algorithms (17 papers) and Topic Modeling (16 papers). The work is most often cited by research in Artificial Intelligence (3.1k citations), Signal Processing (586 citations), Orthopedics and Sports Medicine (358 citations), Computer Vision and Pattern Recognition (938 citations) and Health Information Management (138 citations). Jesse Davis has collaborated with scholars based in Belgium, United States and United Kingdom. Frequent co-authors include Mark Goadrich, Pedro Domingos, Wannes Meert, Jan Van Haaren, Tom Decroos, Guy Van den Broeck, Vı́tor Santos Costa, Nima Taghipour, Daniel Lowd and Stefan Schoenmackers. Their work appears in journals such as Machine Learning, Frontiers in Bioengineering and Biotechnology, Sensors, Lecture notes in computer science and Data Mining and Knowledge Discovery.
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.