| Large magellanic cloud near-infrared synoptic survey. V. Period–luminosity relations of miras W Yuan, LM Macri, S He, JZ Huang, SM Kanbur, CC Ngeow The Astronomical Journal 154 (4), 149, 2017 | 44 | 2017 |
| The M33 Synoptic Stellar Survey. II. Mira Variables W Yuan, S He, LM Macri, J Long, JZ Huang The Astronomical Journal 153 (4), 170, 2017 | 34 | 2017 |
| Characterization of type Ia supernova light curves using principal component analysis of sparse functional data S He, L Wang, JZ Huang The Astrophysical Journal 857 (2), 110, 2018 | 23 | 2018 |
| Multiwavelength Period–Luminosity and Period–Luminosity–Color Relations at Maximum Light for Mira Variables in the Magellanic Clouds A Bhardwaj, S Kanbur, S He, M Rejkuba, N Matsunaga, R de Grijs, ... The Astrophysical Journal 884 (1), 20, 2019 | 22 | 2019 |
| Graphical model selection and estimation for high dimensional tensor data S He, J Yin, H Li, X Wang Journal of Multivariate Analysis 128, 165-185, 2014 | 20 | 2014 |
| Period estimation for sparsely sampled quasi-periodic light curves applied to miras S He, W Yuan, JZ Huang, J Long, LM Macri The Astronomical Journal 152 (6), 164, 2016 | 19 | 2016 |
| A reproducing kernel Hilbert space approach to functional calibration of computer models R Tuo, S He, A Pourhabib, Y Ding, JZ Huang Journal of the American Statistical Association 118 (542), 883-897, 2023 | 8 | 2023 |
| Functional PCA with covariate-dependent mean and covariance structure F Ding, S He, DE Jones, JZ Huang Technometrics 64 (3), 335-345, 2022 | 8 | 2022 |
| Singular-Value Decomposition Feature-Extraction Method for Cost-Performance Prediction S He, J Du, JZ Huang Journal of Computing in Civil Engineering 31 (5), 04017043, 2017 | 4 | 2017 |
| Spline estimation of functional principal components via manifold conjugate gradient algorithm S He, H Ye, K He Statistics and Computing 32 (6), 106, 2022 | 1 | 2022 |
| Functional Principal Subspace Sampling for Large Scale Functional Data Analysis S He, X Yan Electronic Journal of Statistics 16 (1), 2621-2682, 2022 | 1 | 2022 |
| A novel stellar spectrum denoising method based on deep Bayesian modeling X Kang, S He, Y Zhang Research in Astronomy and Astrophysics 21 (7), 169, 2021 | 1 | 2021 |
| Randomized estimation of functional covariance operator via subsampling S He, X Yan Stat 9 (1), e311, 2020 | 1 | 2020 |
| Penalized spline estimation of principal components for sparse functional data: rates of convergence S He, JZ Huang, K He arXiv preprint arXiv:2402.05438, 2024 | | 2024 |
| Channelling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling F Ding, DE Jones, S He, XL Meng arXiv preprint arXiv:2401.00667, 2024 | | 2024 |
| DINE: Decentralized Inexact Newton With Exact Linear Convergence Rate H Ye, S He, X Chang IEEE Transactions on Signal Processing, 2023 | | 2023 |
| Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior S Chen, K He, S He, Y Ni, RKW Wong Technometrics, 2023 | | 2023 |
| Spatial Linear Regression with Covariate Measurement Errors: Inference and Scalable Computation in a Functional Modeling Approach J Cao, S He, B Zhang Journal of Computational and Graphical Statistics, 2023 | | 2023 |
| A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty S He, H Ye, K He Journal of Machine Learning Research 24 (291), 1-69, 2023 | | 2023 |
| Improved Estimation of High-dimensional Additive Models Using Subspace Learning S He, K He, JZ Huang Journal of Computational and Graphical Statistics 31 (3), 866-876, 2022 | | 2022 |
Jianhua Z. HuangSchool of Data Science, Chinese University of Hong Kong, ShenzhenVerified email at cuhk.edu.cn
