| Functional graphical models X Qiao, S Guo, GM James Journal of the American Statistical Association 114 (525), 211-222, 2019 | 106 | 2019 |
| Doubly functional graphical models in high dimensions X Qiao, C Qian, GM James, S Guo Biometrika 107 (2), 415-431, 2020 | 44 | 2020 |
| Homogeneity pursuit in single index models based panel data analysis H Lian, X Qiao, W Zhang Journal of Business & Economic Statistics 39 (2), 386-401, 2021 | 22 | 2021 |
| Index models for sparsely sampled functional data P Radchenko, X Qiao, GM James Journal of the American Statistical Association 110 (510), 824-836, 2015 | 21 | 2015 |
| An autocovariance-based learning framework for high-dimensional functional time series J Chang, C Chen, X Qiao, Q Yao Journal of Econometrics 239 (2), 105385, 2024 | 18 | 2024 |
| Functional linear regression: dependence and error contamination C Chen, S Guo, X Qiao Journal of Business & Economic Statistics 40 (1), 444-457, 2022 | 17 | 2022 |
| On consistency and sparsity for high-dimensional functional time series with application to autoregressions S Guo, X Qiao Bernoulli 29 (1), 451-472, 2023 | 16 | 2023 |
| Factor modelling for high-dimensional functional time series S Guo, X Qiao, Q Wang arXiv preprint arXiv:2112.13651, 2021 | 12 | 2021 |
| Finite sample theory for high-dimensional functional/scalar time series with applications Q Fang, S Guo, X Qiao Electronic Journal of Statistics 16 (1), 527-591, 2022 | 11 | 2022 |
| Adaptive functional thresholding for sparse covariance function estimation in high dimensions Q Fang, S Guo, X Qiao Journal of the American Statistical Association, 1-13, 2023 | 4 | 2023 |
| Factor-guided estimation of large covariance matrix function with conditional functional sparsity D Li, X Qiao, Z Wang arXiv preprint arXiv:2311.02450, 2023 | 2 | 2023 |
| CATVI: Conditional and adaptively truncated variational inference for hierarchical bayesian nonparametric models Y Liu, X Qiao, J Lam International Conference on Artificial Intelligence and Statistics, 3647-3662, 2022 | 2 | 2022 |
| From sparse to dense functional data in high dimensions: Revisiting phase transitions from a non-asymptotic perspective S Guo, D Li, X Qiao, Y Wang arXiv preprint arXiv:2306.00476, 2023 | 1 | 2023 |
| EEGNN: edge enhanced graph neural network with a Bayesian nonparametric graph model Y Liu, X Qiao, L Wang, J Lam International Conference on Artificial Intelligence and Statistics, 2132-2146, 2023 | 1 | 2023 |
| Supplement to “On consistency and sparsity for high-dimensional functional time series with application to autoregressions.” S Guo, X Qiao | 1 | 2023 |
| Conditional variational inference with adaptive truncation for Bayesian nonparametric models JY Liu, X Qiao arXiv preprint arXiv:2001.04508, 2020 | 1 | 2020 |
| A General Theory for Large-Scale Curve Time Series via Functional Stability Measure S Guo, X Qiao arXiv preprint arXiv:1812.07619, 2018 | 1 | 2018 |
| DF2M: An Explainable Deep Bayesian Nonparametric Model for High-Dimensional Functional Time Series Y Liu, X Qiao, Y Pei, L Wang arXiv preprint arXiv:2305.14543, 2023 | | 2023 |
| EEGNN: Edge Enhanced Graph Neural Networks. Y Liu, X Qiao, L Wang, J Lam CoRR, 2022 | | 2022 |
| Sparseness in functional data analysis X Qiao University of Southern California, 2015 | | 2015 |
