| Little's test of missing completely at random C Li The Stata Journal 13 (4), 795-809, 2013 | 652 | 2013 |
| Scalable Bayes via Barycenter in Wasserstein Space S Srivastava, C Li, DB Dunson Journal of Machine Learning Research 19 (8), 1-35, 2018 | 190 | 2018 |
| Simple, Scalable and Accurate Posterior Interval Estimation C Li, S Srivastava, DB Dunson Biometrika 104 (3), 665-680. arXiv:1605.04029., 2017 | 70 | 2017 |
| Distributed Bayesian Inference in Massive Spatial Data R Guhaniyogi, C Li, T Savitsky, S Srivastava Statistical Science 38 (2), 262-284, arXiv:1712.09767., 2023 | 46* | 2023 |
| Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior R Guhaniyogi, C Li, TD Savitsky, S Srivastava Journal of Machine Learning Research 23 (84), 1-59, arXiv:2006.00783, 2022 | 26 | 2022 |
| On oracle property and asymptotic validity of Bayesian generalized method of moments C Li, W Jiang Journal of Multivariate Analysis 145, 132-147, 2016 | 24* | 2016 |
| Interpretable biomanufacturing process risk and sensitivity analyses for quality-by-design and stability control W Xie, B Wang, C Li, D Xie, J Auclair Naval Research Logistics 69 (3), 461-483, arXiv:1909.04261, 2022 | 21* | 2022 |
| A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation W Xie, C Li, Y Wu, P Zhang SIAM/ASA Journal on Uncertainty Quantification 9 (4), 1527-1552, arXiv:1910 …, 2021 | 16* | 2021 |
| Bayesian Fixed-domain Asymptotics for Covariance Parameters in a Gaussian Process Model C Li Annals of Statistics 50 (6), 3334-3363, arXiv:2010.02126, 2022 | 14* | 2022 |
| On Posterior Consistency of Tail Index for Bayesian Kernel Mixture Models C Li, L Lin, DB Dunson Bernoulli 25 (3), 1999-2028, arXiv:1511.02775, 2019 | 12* | 2019 |
| General oracle inequalities for Gibbs posterior with application to ranking C Li, W Jiang, M Tanner Conference on Learning Theory, 512-521, 2013 | 12 | 2013 |
| A Factor-Based Bayesian Framework for Risk Analysis in Stochastic Simulations W Xie, C Li, P Zhang ACM Transactions on Modeling and Computer Simulation (TOMACS) 27, Article 27, 2017 | 9 | 2017 |
| Radial neighbors for provably accurate scalable approximations of Gaussian processes Y Zhu, M Peruzzi, C Li, DB Dunson Biometrika 111 (4), 1151-1167, arXiv:2211.14692, 2024 | 7 | 2024 |
| Modeling recurrent failures on large directed networks Q Zhai, Z Ye, C Li, M Revie, DB Dunson Journal of the American Statistical Association, 2024 | 7 | 2024 |
| Rate analysis for offline simulation online application S Gao, C Li, J Du 2019 Winter Simulation Conference (WSC), 3468-3479, 2019 | 7 | 2019 |
| Quantifying statistical uncertainty for dependent input models with factor structure W Xie, C Li, H Sun Proceedings of the 2015 Winter Simulation Conference, 667-678, 2015 | 7 | 2015 |
| Classification Trees for Imbalanced Data: Surface-to-Volume Regularization Y Zhu, C Li, DB Dunson Journal of the American Statistical Association 118 (543), 1707-1717, arXiv …, 2023 | 4 | 2023 |
| On Bayesian Oracle Properties W Jiang, C Li Bayesian Analysis 14 (1), 235-260, arXiv:1507.05723, 2019 | 4* | 2019 |
| General inequalities for Gibbs posterior with nonadditive empirical risk C Li, W Jiang, MA Tanner Econometric Theory 30 (6), 1247-1271, 2014 | 4 | 2014 |
| Fixed-domain posterior contraction rates for spatial Gaussian process model with nugget C Li, S Sun, Y Zhu Journal of the American Statistical Association 119 (546), 1336-1347, arXiv …, 2024 | 3 | 2024 |
David DunsonArts & Sciences Professor of Statistical Science & MathematicsGeverifieerd e-mailadres voor duke.edu