| Autodiff: combining auto-encoder and diffusion model for tabular data synthesizing N Suh, X Lin, DY Hsieh, M Honarkhah, G Cheng NeurIPS SyntheticData4ML workshop, 2023 | 31 | 2023 |
| A survey on statistical theory of deep learning: Approximation, training dynamics, and generative models N Suh, G Cheng Annual Review of Statistics and Its Application 12 (1), 177-207, 2025 | 24 | 2025 |
| TimeAutoDiff: A Unified Framework for Generation, Imputation, Forecasting, and Time-Varying Metadata Conditioning of Heterogeneous Time Series Tabular Data N Suh, Y Yang, DY Hsieh, Q Luan, S Xu, S Zhu, G Cheng TMLR, 2025 | 24* | 2025 |
| Benefits of transformer: In-context learning in linear regression tasks with unstructured data Y Xing, X Lin, N Suh, Q Song, G Cheng arXiv preprint arXiv:2402.00743, 2024 | 17* | 2024 |
| A non-parametric regression viewpoint: Generalization of overparametrized deep relu network under noisy observations N Suh, H Ko, X Huo ICLR, 2021 | 17 | 2021 |
| Asymptotic Theory of -Regularized PDE Identification from a Single Noisy Trajectory Y He, N Suh, X Huo, SH Kang, Y Mei SIAM/ASA Journal on Uncertainty Quantification 10 (3), 1012-1036, 2022 | 14 | 2022 |
| Approximation and non-parametric estimation of functions over high-dimensional spheres via deep ReLU networks N Suh, TY Zhou, X Huo ICLR, 2022 | 9 | 2022 |
| Discriminative estimation of total variation distance: A fidelity auditor for generative data L Tao, S Xu, CH Wang, N Suh, G Cheng arXiv preprint arXiv:2405.15337, 2024 | 6 | 2024 |
| Approximation of rkhs functionals by neural networks TY Zhou, N Suh, G Cheng, X Huo arXiv preprint arXiv:2403.12187, 2024 | 4 | 2024 |
| Fused LassoNet: Sequential feature selection for spectral data with neural networks C Yeo, N Suh, Y Kim Chemometrics and Intelligent Laboratory Systems 257, 105315, 2025 | 2 | 2025 |
| On excess risk convergence rates of neural network classifiers H Ko, N Suh, X Huo arXiv preprint arXiv:2309.15075, 2023 | 2 | 2023 |
| High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization N Suh, LH Lin, X Huo Journal of Computational and Graphical Statistics, 1-21, 2024 | 1 | 2024 |
| Adaptive Online Monitoring of the Ising model. N Suh, R Zhang, Y Mei Allerton, 426-431, 2019 | 1 | 2019 |
| Review on Parameter Estimation in HMRF N Suh arXiv preprint arXiv:1711.07561, 2017 | 1 | 2017 |
| Statistical viewpoints on network model, PDE Identification, low-rank matrix estimation and deep learning N Suh Georgia Institute of Technology, 2022 | | 2022 |
| A network model that combines latent factors and sparse graphs N Suh, X Huo, E Heim, L Seversky Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (2 …, 2021 | | 2021 |
| SAMoE-VAE: A Tabular Foundation Model with a Schema-Aware Mixture-of-Experts Variational Autoencoder X Lin, C Wang, M GUI, N Suh, J Byun, O Chen, Z DeSoto, Y Cho, ... | | |
Xiaoming HuoProfessor, Georgia Institute of TechnologyVerified email at gatech.edu
