A closer look at the personality-turnover relationship: Criterion expansion, dark traits, and time SE Woo, M Chae, AT Jebb, Y Kim Journal of Management 42 (2), 357-385, 2016 | 44 | 2016 |
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models M Chae, D Kim, Y Kim, L Lin Journal of Machine Learning Research 24 (77), 1-42, 2023 | 16 | 2023 |
Wasserstein upper bounds of the total variation for smooth densities M Chae, SG Walker Statistics & Probability Letters 163, 108771, 2020 | 16 | 2020 |
Bayesian sparse linear regression with unknown symmetric error M Chae, L Lin, DB Dunson Information and Inference: A Journal of the IMA 8 (3), 621-653, 2019 | 15 | 2019 |
Additive time-dependent hazard model with doubly truncated data G Frank, M Chae, Y Kim Journal of the Korean Statistical Society 48 (2), 179-193, 2019 | 10 | 2019 |
The semi-parametric Bernstein-von Mises theorem for regression models with symmetric errors M Chae, Y Kim, B Kleijn Statistica Sinica 29 (3), 1465-1487, 2019 | 10 | 2019 |
On an algorithm for solving Fredholm integrals of the first kind M Chae, R Martin, SG Walker Statistics and Computing 29, 645-654, 2019 | 9 | 2019 |
Convergence of an iterative algorithm to the nonparametric MLE of a mixing distribution M Chae, R Martin, SG Walker Statistics & Probability Letters 140, 142-146, 2018 | 9* | 2018 |
Documents recommendation using large citation data M Chae, M Kang, Y Kim Journal of the Korean Data and Information Science Society 24 (5), 999-1011, 2013 | 9 | 2013 |
Posterior asymptotics in Wasserstein metrics on the real line M Chae, P De Blasi, SG Walker Electronic Journal of Statistics 15 (2), 3635-3677, 2021 | 8 | 2021 |
An online gibbs sampler algorithm for hierarchical dirichlet processes prior Y Kim, M Chae, K Jeong, B Kang, H Chung ECML PKDD 2016, 509-523, 2016 | 7 | 2016 |
Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks M Chae arXiv preprint arXiv:2202.02890, 2022 | 5 | 2022 |
Bayesian consistency for a nonparametric stationary Markov model M Chae, SG Walker Bernoulli 25 (2), 877-901, 2019 | 5 | 2019 |
A novel approach to Bayesian consistency M Chae, SG Walker Bernoulli 11 (2), 4723-4745, 2017 | 5 | 2017 |
An EM-based iterative method for solving large sparse linear systems M Chae, SG Walker Linear and Multilinear Algebra 68 (1), 45-62, 2020 | 4 | 2020 |
The semiparametric Bernstein-von Mises theorem for models with symmetric error M Chae Seoul National University, 2015 | 4 | 2015 |
Online learning for the Dirichlet process mixture model via weakly conjugate approximation K Jeong, M Chae, Y Kim Computational Statistics & Data Analysis 179, 107626, 2023 | 3 | 2023 |
Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors K Lee, M Chae, L Lin Journal of the Korean Statistical Society 50 (2), 511-527, 2021 | 2 | 2021 |
A mixture of beta–Dirichlet processes prior for Bayesian analysis of event history data M Chae, R Weißbach, KH Cho, Y Kim Journal of the Korean Statistical Society 42 (3), 313-321, 2013 | 2 | 2013 |
Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable HK Kwon, M Chae International Conference on Artificial Intelligence and Statistics, 469-477, 2024 | 1 | 2024 |