Stephen Bates
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods in Clinical Trials
- Statistical Methods and Bayesian Inference
Papers in
-
- Adversarial Robustness in Machine Learning 3
- Explainable Artificial Intelligence (XAI) 2
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- Gene expression and cancer classification 2
- Co-authors
- Trevor Hastie (1 shared paper)Robert Tibshirani (1 shared paper)Emmanuel J. Candès (7 shared papers)Matteo Sesia (4 shared papers)Chiara Sabatti (3 shared papers)Michael I. Jordan (5 shared papers)Anastasios N. Angelopoulos (4 shared papers)Clara Fannjiang (2 shared papers)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)The Annals of Applied Statistics (1 paper)Academic Medicine (1 paper)Journal of the American Statistical Association (1 paper)Remote Sensing of Environment (1 paper)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Stephen Bates
15 papers receiving 538 citations
Stephen Bates's Hit Papers
Peers
Comparison fields: 5 of 127
- Statistics and Probability 100
- Health Informatics 8
- Artificial Intelligence 139
- Statistics, Probability and Uncertainty 20
- Gender Studies 25
Countries citing papers authored by Stephen Bates
This map shows the geographic impact of Stephen Bates'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 Stephen Bates with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Bates more than expected).
Fields of papers citing papers by Stephen Bates
This network shows the impact of papers produced by Stephen Bates. 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 Stephen Bates. The network helps show where Stephen Bates may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen Bates, 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 | Cross-Validation: What Does It Estimate and How Well Does It Do It? Hit paper breakdown → | 2023 | 208 |
| 2 | 2010 | 78 | |
| 3 | 2021 | 47 | |
| 4 | 2023 | 40 | |
| 5 | 2020 | 40 | |
| 6 | 2020 | 37 | |
| 7 | 2023 | 37 | |
| 8 | 2020 | 23 | |
| 9 | 2022 | 23 | |
| 10 | 2023 | 6 | |
| 11 | 2025 | 4 | |
| 12 | 2022 | 3 | |
| 13 | 1995 | 3 | |
| 14 | 2025 | 1 | |
| 15 | Achieving Equalized Odds by Resampling Sensitive Attributes | 2020 | 1 |
About Stephen Bates
Stephen Bates is a scholar working on Artificial Intelligence, Molecular Biology, Genetics, Statistics and Probability and Statistics, Probability and Uncertainty, having authored 15 papers that have together received 551 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (3 papers), Statistical Methods and Inference (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Genetic Associations and Epidemiology (3 papers), Gene expression and cancer classification (2 papers), Genetic and phenotypic traits in livestock (2 papers), Advanced Statistical Process Monitoring (2 papers) and Explainable Artificial Intelligence (XAI) (2 papers). The work is most often cited by research in Statistics and Probability (100 citations), Health Informatics (8 citations), Artificial Intelligence (139 citations), Statistics, Probability and Uncertainty (20 citations) and Gender Studies (25 citations). Stephen Bates has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Trevor Hastie, Robert Tibshirani, Emmanuel J. Candès, Matteo Sesia, Chiara Sabatti, Michael I. Jordan, Anastasios N. Angelopoulos, Clara Fannjiang, Lucas Janson and Jonathan Marchini. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Annals of Applied Statistics, Academic Medicine, Journal of the American Statistical Association and Remote Sensing of Environment.
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.