| Smooth function approximation by deep neural networks with general activation functions I Ohn, Y Kim Entropy 21 (7), 627, 2019 | 114 | 2019 |
| Fast convergence rates of deep neural networks for classification Y Kim, I Ohn, D Kim Neural Networks 138, 179-197, 2021 | 98 | 2021 |
| Generalizing uncertainty decomposition theory in climate change impact assessments Y Kim, I Ohn, JK Lee, YO Kim Journal of Hydrology X 3, 100024, 2019 | 33 | 2019 |
| Nonconvex sparse regularization for deep neural networks and its optimality I Ohn, Y Kim Neural computation 34 (2), 476-517, 2022 | 25 | 2022 |
| Optimal Bayesian estimation of Gaussian mixtures with growing number of components I Ohn, L Lin Bernoulli 29 (2), 1195-1218, 2023 | 18 | 2023 |
| Learning fair representation with a parametric integral probability metric D Kim, K Kim, I Kong, I Ohn, Y Kim International Conference on Machine Learning, 11074-11101, 2022 | 18 | 2022 |
| Adaptive variational Bayes: Optimality, computation and applications I Ohn, L Lin The Annals of Statistics 52 (1), 335-363, 2024 | 15 | 2024 |
| Posterior consistency of factor dimensionality in high-dimensional sparse factor models I Ohn, Y Kim Bayesian Analysis 17 (2), 491-514, 2022 | 11 | 2022 |
| Uncertainty decomposition in climate-change impact assessments: a Bayesian perspective I Ohn, SB Seo, S Kim, YO Kim, Y Kim Communications for Statistical Applications and Methods 27 (1), 109-128, 2020 | 8 | 2020 |
| Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting Y Kim, W Kim, I Ohn, YO Kim CSAM (Communications for Statistical Applications and Methods) 24 (1), 67-80, 2017 | 8 | 2017 |
| Masked Bayesian neural networks: Theoretical guarantee and its posterior inference I Kong, D Yang, J Lee, I Ohn, G Baek, Y Kim International conference on machine learning, 17462-17491, 2023 | 6 | 2023 |
| Bayesian nonparametric latent class analysis for different item types M Qiu, S Paganin, I Ohn, L Lin Multivariate Behavioral Research 58 (1), 156-157, 2023 | 6 | 2023 |
| SLIDE: A surrogate fairness constraint to ensure fairness consistency K Kim, I Ohn, S Kim, Y Kim Neural Networks 154, 441-454, 2022 | 6 | 2022 |
| Long-term simulation and uncertainty quantification of water temperature in Soyanggang reservoir due to climate change Y Yun, H Park, S Chung, Y Kim, I Ohn, S Lee Journal of Korean Society on Water Environment 36 (1), 14-28, 2020 | 5 | 2020 |
| A Bayesian sparse factor model with adaptive posterior concentration I Ohn, L Lin, Y Kim Bayesian Analysis 19 (4), 1277-1301, 2024 | 3 | 2024 |
| Intrinsic and extrinsic deep learning on manifolds Y Fang, I Ohn, V Gupta, L Lin Electronic Journal of Statistics 18 (1), 1160-1184, 2024 | 2 | 2024 |
| Intrinsic and extrinsic deep learning on manifolds Y Fang, I Ohn, V Gupta, L Lin arXiv preprint arXiv:2302.08606, 2023 | 2 | 2023 |
| Model-wise uncertainty decomposition in multi-model ensemble hydrological projections I Ohn, S Kim, SB Seo, YO Kim, Y Kim Stochastic Environmental Research and Risk Assessment 35 (12), 2549-2565, 2021 | 2 | 2021 |
| Bayesian uncertainty decomposition for hydrological projections I Ohn, S Kim, SB Seo, YO Kim, Y Kim Journal of the Korean Statistical Society 49, 953-975, 2020 | 2 | 2020 |
| Uncertainty decomposition by scenarios in water resource projections† J Lee, I Ohn, Y Kim The Korean Data & Information Science Society 29 (6), 1469-1480, 2018 | 2 | 2018 |
