Benjamin Letham
Impact in
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- Stock Market Forecasting Methods
- Forecasting Techniques and Applications
- Health Informatics top 5%
Papers in
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- Rough Sets and Fuzzy Logic 6
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- Advanced Bandit Algorithms Research 3
- Co-authors
- Sean J. TaylorCynthia RudinDavid MadiganTyler H. McCormickEytan BakshyBrian KarrerDaniel JiangMaximilian Balandat
- Journals
- European Journal of Neuroscience (1 paper)The Annals of Applied Statistics (1 paper)Data Mining and Knowledge Discovery (1 paper)Machine Learning (1 paper)The American Statistician (1 paper)
- Partner nations
- United StatesIsraelFinland
In The Last Decade
Benjamin Letham
22 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Management Science and Operations Research 431
- Health Informatics 46
- Signal Processing 253
- Artificial Intelligence 713
- Modeling and Simulation 81
Countries citing papers authored by Benjamin Letham
This map shows the geographic impact of Benjamin Letham'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 Benjamin Letham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Letham more than expected).
Fields of papers citing papers by Benjamin Letham
This network shows the impact of papers produced by Benjamin Letham. 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 Benjamin Letham. The network helps show where Benjamin Letham may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamin Letham, 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 | 2024 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 6 | |
| 5 | Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization | 2020 | 2 |
| 6 | High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization | 2020 | 3 |
| 7 | BoTorch: Programmable Bayesian Optimization in PyTorch. | 2019 | 32 |
| 8 | Forecasting at Scale Hit paper breakdown → | 2017 | 1272 |
| 9 | 2017 | 35 | |
| 10 | 2016 | 6 | |
| 11 | Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model Hit paper breakdown → | 2015 | 414 |
| 12 | Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data | 2014 | 13 |
| 13 | 2013 | 34 | |
| 14 | 2013 | 5 | |
| 15 | Similarity-Weighted Association Rules for a Name Recommender System | 2013 | 1 |
| 16 | A Learning Theory Framework for Sequential Event Prediction and Association Rules | 2012 | 3 |
| 17 | Sequential Event Prediction with Association Rules | 2011 | 29 |
| 18 | 2011 | 2 | |
| 19 | 2010 | 12 | |
| 20 | 2010 | 106 |
About Benjamin Letham
Benjamin Letham is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research, Artificial Intelligence, Information Systems and Signal Processing, having authored 24 papers that have together received 2.1k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (6 papers), Data Mining Algorithms and Applications (4 papers), Imbalanced Data Classification Techniques (4 papers), Machine Learning and Data Classification (3 papers), Gaussian Processes and Bayesian Inference (3 papers), Recommender Systems and Techniques (3 papers), Advanced Bandit Algorithms Research (3 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Management Science and Operations Research (431 citations), Health Informatics (46 citations), Signal Processing (253 citations), Artificial Intelligence (713 citations) and Modeling and Simulation (81 citations). Benjamin Letham has collaborated with scholars based in United States, Israel and Finland. Frequent co-authors include Sean J. Taylor, Cynthia Rudin, David Madigan, Tyler H. McCormick, Eytan Bakshy, Brian Karrer, Daniel Jiang, Maximilian Balandat, Samuel Daulton and Andrew Gordon Wilson. Their work appears in journals such as European Journal of Neuroscience, The Annals of Applied Statistics, Data Mining and Knowledge Discovery, Machine Learning and The American Statistician.
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.