Forecasting urban household water demand with statistical and machine learning methods using large space-time data: A Comparative study I Duerr, HR Merrill, C Wang, R Bai, M Boyer, MD Dukes, N Bliznyuk Environmental Modelling & Software 102, 29-38, 2018 | 71 | 2018 |
Spike-and-slab group lassos for grouped regression and sparse generalized additive models R Bai, GE Moran, JL Antonelli, Y Chen, MR Boland Journal of the American Statistical Association 117, 184–197, 2022 | 55 | 2022 |
High-dimensional multivariate posterior consistency under global–local shrinkage priors R Bai, M Ghosh Journal of Multivariate Analysis 167, 157-170, 2018 | 41 | 2018 |
Spike-and-Slab Meets LASSO: A Review of the Spike-and-Slab LASSO R Bai, V Ročková, EI George Handbook of Bayesian Variable Selection, 81-108, 2021 | 37 | 2021 |
VCBART: Bayesian trees for varying coefficients SK Deshpande, R Bai, C Balocchi, JE Starling, J Weiss arXiv preprint arXiv:2003.06416, 2020 | 32 | 2020 |
Individual-Level and Neighborhood-Level Risk Factors for Severe Maternal Morbidity JR Meeker, SP Canelón, R Bai, LD Levine, MR Boland Obstetrics & Gynecology 137, 847-854, 2021 | 28 | 2021 |
On the beta prime prior for Scale Parameters in High-Dimensional Bayesian Regression models R Bai, M Ghosh Statistica Sinica 31, 843-865, 2021 | 25 | 2021 |
Large-Scale Multiple Hypothesis Testing with the Normal-Beta Prime Prior R Bai, M Ghosh Statistics 53, 1210-1233, 2019 | 25* | 2019 |
Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance R Bai, MR Boland, Y Chen Journal of Machine Learning Research 24 (259), 1-49, 2023 | 16* | 2023 |
Association of Neighborhood-Level Factors and COVID-19 Infection Patterns in Philadelphia Using Spatial Regression MR Boland, J Liu, C Balocchi, J Meeker, R Bai, I Mellis, DL Mowery, ... AMIA Annual Symposium Proceedings 2021, 545-554, 2021 | 15 | 2021 |
Bayesian group regularization in generalized linear models with a continuous spike-and-slab prior R Bai arXiv preprint arXiv:2007.07021, 2020 | 9* | 2020 |
A Robust Bayesian Copas Selection Model for Quantifying and Correcting Publication Bias R Bai, L Lin, MR Boland, Y Chen arXiv preprint arXiv:2005.02930, 2020 | 6 | 2020 |
Neighborhood deprivation increases the risk of Post-induction cesarean delivery JR Meeker, HH Burris, R Bai, LD Levine, MR Boland Journal of the American Medical Informatics Association 29, 329-334, 2022 | 4 | 2022 |
Generative quantile regression with variability penalty S Wang, M Shin, R Bai Journal of Computational and Graphical Statistics, 1-21, 2024 | 3 | 2024 |
Corrigendum to “High-dimensional multivariate posterior consistency under global-local shrinkage priors”[J. Multivariate Anal. 167 (2018) 157-170] SH Wang, R Bai, HH Huang | 2 | 2023 |
Two-Step Mixed-Type Multivariate Bayesian Sparse Variable Selection with Shrinkage Priors SH Wang, R Bai, HH Huang arXiv preprint arXiv:2201.12839, 2022 | 2* | 2022 |
Bayesian modal regression based on mixture distributions Q Liu, X Huang, R Bai Computational Statistics & Data Analysis, 108012, 2024 | 1 | 2024 |
Fast Bootstrapping Nonparametric Maximum Likelihood for Latent Mixture Models S Wang, M Shin, R Bai IEEE Signal Processing Letters 31, 870-874, 2024 | 1 | 2024 |
Quantifying patient and neighborhood risks for stillbirth and preterm birth in Philadelphia with a Bayesian spatial model C Balocchi, R Bai, J Liu, SP Canelón, EI George, Y Chen, MR Boland arXiv e-prints, arXiv: 2105.04981, 2021 | 1* | 2021 |
Neural-g: A Deep Learning Framework for Mixing Density Estimation S Wang, S Chakraborty, Q Qin, R Bai arXiv preprint arXiv:2406.05986, 2024 | | 2024 |