| Sure independence screening in generalized linear models with NP-dimensionality J Fan, R Song | 852 | 2010 |
| Nonparametric independence screening in sparse ultra-high-dimensional additive models J Fan, Y Feng, R Song Journal of the American Statistical Association 106 (494), 544-557, 2011 | 714 | 2011 |
| Cardiac resynchronization therapy reduces the risk of hospitalizations in patients with advanced heart failure: results from the Comparison of Medical Therapy, Pacing and … IS Anand, P Carson, E Galle, R Song, J Boehmer, JK Ghali, B Jaski, ... Circulation 119 (7), 969-977, 2009 | 250 | 2009 |
| Doubly robust learning for estimating individualized treatment with censored data YQ Zhao, D Zeng, EB Laber, R Song, M Yuan, MR Kosorok Biometrika 102 (1), 151-168, 2015 | 215 | 2015 |
| A review on graph neural network methods in financial applications J Wang, S Zhang, Y Xiao, R Song arXiv preprint arXiv:2111.15367, 2021 | 214 | 2021 |
| High-dimensional A-learning for optimal dynamic treatment regimes C Shi, A Fan, R Song, W Lu Annals of statistics 46 (3), 925, 2018 | 147 | 2018 |
| Censored rank independence screening for high-dimensional survival data R Song, W Lu, S Ma, X Jessie Jeng Biometrika 101 (4), 799-814, 2014 | 143 | 2014 |
| Statistical inference of the value function for reinforcement learning in infinite-horizon settings C Shi, S Zhang, W Lu, R Song Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 139 | 2022 |
| Penalized q-learning for dynamic treatment regimens R Song, W Wang, D Zeng, MR Kosorok Statistica Sinica 25 (3), 901, 2015 | 136 | 2015 |
| Asfm-net: Asymmetrical siamese feature matching network for point completion Y Xia, Y Xia, W Li, R Song, K Cao, U Stilla Proceedings of the 29th ACM international conference on multimedia, 1938-1947, 2021 | 115 | 2021 |
| Doubly robust inference when combining probability and non-probability samples with high dimensional data S Yang, JK Kim, R Song Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020 | 113 | 2020 |
| Quantile-optimal treatment regimes L Wang, Y Zhou, R Song, B Sherwood Journal of the American Statistical Association 113 (523), 1243-1254, 2018 | 111 | 2018 |
| Federated learning via decentralized dataset distillation in resource-constrained edge environments R Song, D Liu, DZ Chen, A Festag, C Trinitis, M Schulz, A Knoll 2023 International Joint Conference on Neural Networks (IJCNN), 1-10, 2023 | 99 | 2023 |
| Inference under right censoring for transformation models with a change-point based on a covariate threshold MR Kosorok, R Song | 95 | 2007 |
| A massive data framework for M-estimators with cubic-rate C Shi, W Lu, R Song Journal of the American Statistical Association 113 (524), 1698-1709, 2018 | 93 | 2018 |
| On Estimation of Optimal Treatment Regimes for Maximizing t-Year Survival Probability R Jiang, W Lu, R Song, M Davidian Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 92 | 2017 |
| Dynamic causal effects evaluation in a/b testing with a reinforcement learning framework C Shi, X Wang, S Luo, H Zhu, J Ye, R Song Journal of the American Statistical Association 118 (543), 2059-2071, 2023 | 80 | 2023 |
| Linear hypothesis testing for high dimensional generalized linear models C Shi, R Song, Z Chen, R Li Annals of statistics 47 (5), 2671, 2019 | 79 | 2019 |
| Concordance-assisted learning for estimating optimal individualized treatment regimes C Fan, W Lu, R Song, Y Zhou Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 73 | 2017 |
| Characterization and microfabrication of natural porous rocks: From micro-CT imaging and digital rock modelling to micro-3D-printed rock analogs R Song, Y Wang, S Sun, J Liu Journal of Petroleum Science and Engineering 205, 108827, 2021 | 72 | 2021 |
