| False discovery rate control via data splitting C Dai, B Lin, X Xing, JS Liu Journal of the American Statistical Association 118 (544), 2503-2520, 2023 | 49 | 2023 |
| An invitation to sequential Monte Carlo samplers C Dai, J Heng, PE Jacob, N Whiteley Journal of the American Statistical Association 117 (539), 1587-1600, 2022 | 49 | 2022 |
| A scale-free approach for false discovery rate control in generalized linear models C Dai, B Lin, X Xing, JS Liu Journal of the American Statistical Association 118 (543), 1551-1565, 2023 | 23 | 2023 |
| Monte Carlo approximation of Bayes factors via mixing with surrogate distributions C Dai, JS Liu Journal of the American Statistical Association 117 (538), 765-780, 2022 | 7 | 2022 |
| Interpretable selection and visualization of features and interactions using bayesian forests V Krakovna, C Dai, JS Liu Statistics and Its Interface 11, 503-513, 2018 | 5 | 2018 |
| Wang-Landau algorithm as stochastic optimization and its acceleration C Dai, JS Liu Physical Review E 101 (3), 033301, 2020 | 3 | 2020 |
| Late 19th century navigational uncertainties and their influence on sea surface temperature estimates C Dai, D Chan, P Huybers, N Pillai | 2 | 2021 |
| NGM: Neural Gaussian Mirror for Controlled Feature Selection in Neural Networks X Xing, Y Gui, C Dai, JS Liu 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 2 | 2020 |
| Metropolis Jumping Rules JS Liu, C Dai Wiley StatsRef: Statistics Reference Online, 1-12, 2014 | 1 | 2014 |
| Methods on Model Selection: Bayes Factor Approximation and False Discovery Rate Control C Dai Harvard University, 2020 | | 2020 |
Jun S LiuProfessor of statistics, Harvard UniversityVerified email at stat.harvard.edu
