Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2019/03/22
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Journal
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Indian UGC (journal)
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Refrences42
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Citations23
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V. Roshan Joseph H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA;
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Dianpeng Wang School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China;
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Li Gu Amazon.com, Inc., Seattle, WA;
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Shiji Lyu Department of Mathematics, Princeton University, Princeton, NJ;
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Rui Tuo Department of Industrial & Systems Engineering, Texas A& M University, College Station, TX
Cite
Joseph, V. Roshan, et al. “Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs”. Technometrics, vol. 61, no. 3, 2019, pp. 297-08, https://doi.org/10.1080/00401706.2018.1552203.
Joseph, V. R., Wang, D., Gu, L., Lyu, S., & Tuo, R. (2019). Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs. Technometrics, 61(3), 297-308. https://doi.org/10.1080/00401706.2018.1552203
Joseph, V. Roshan, Dianpeng Wang, Li Gu, Shiji Lyu, and Rui Tuo. “Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs”. Technometrics 61, no. 3 (2019): 297-308. https://doi.org/10.1080/00401706.2018.1552203.
Joseph VR, Wang D, Gu L, Lyu S, Tuo R. Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs. Technometrics. 2019;61(3):297-308.
Journal Categories
Science
Mathematics
Science
Mathematics
Probabilities
Mathematical statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Proceedings of the 35th International Conference on Machine Learning | 2018 | |||
| International Conference on Machine Learning | 2016 | |||
| International Conference on Machine Learning | 2016 | |||
| International Conference on Machine Learning | 2015 | |||
| International Conference on Machine Learning | 2003 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Non‐uniform active learning for Gaussian process models with applications to trajectory informed aerodynamic databases | Statistical Analysis and Data Mining: The ASA Data Science Journal |
| 2024 | |
| The resampling method via representative points | Statistical Papers |
| 2024 | |
| A novel batch-selection strategy for parallel global optimization | Engineering Optimization |
| 2024 | |
| A review on design inspired subsampling for big data | Statistical Papers |
| 10 | 2023 |
| Deterministic sampling based on Kullback–Leibler divergence and its applications | Statistical Papers |
| 2023 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 16
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Constrained minimum energy designs and was published in 2021. The most recent citation comes from a 2024 study titled A novel batch-selection strategy for parallel global optimization. This article reached its peak citation in 2022, with 10 citations. It has been cited in 15 different journals, 13% of which are open access. Among related journals, the Statistical Papers cited this research the most, with 6 citations. The chart below illustrates the annual citation trends for this article.