| The spike-and-slab lasso V Ročková, EI George Journal of the American Statistical Association 113 (521), 431-444, 2018 | 448 | 2018 |
| EMVS: The EM approach to Bayesian variable selection V Ročková, EI George Journal of the American Statistical Association 109 (506), 828-846, 2014 | 346 | 2014 |
| Mutant DNMT3A: a marker of poor prognosis in acute myeloid leukemia AFT Ribeiro, M Pratcorona, C Erpelinck-Verschueren, V Rockova, ... Blood, The Journal of the American Society of Hematology 119 (24), 5824-5831, 2012 | 340 | 2012 |
| Risk stratification of intermediate-risk acute myeloid leukemia: integrative analysis of a multitude of gene mutation and gene expression markers V Rockova, S Abbas, BJ Wouters, CAJ Erpelinck, HB Beverloo, R Delwel, ... Blood, The Journal of the American Society of Hematology 118 (4), 1069-1076, 2011 | 145 | 2011 |
| Posterior concentration for Bayesian regression trees and forests V Ročková, S Van der Pas The Annals of Statistics 48 (4), 2108-2131, 2020 | 142* | 2020 |
| Fast Bayesian factor analysis via automatic rotations to sparsity V Ročková, EI George Journal of the American Statistical Association 111 (516), 1608-1622, 2016 | 142 | 2016 |
| Bayesian estimation of sparse signals with a continuous spike-and-slab prior V Ročková | 135 | 2018 |
| Deregulated Expression of EVI1 Defines a Poor Prognostic Subset of MLL-Rearranged Acute Myeloid Leukemias: A Study of the German-Austrian Acute Myeloid … S Groeschel, RF Schlenk, J Engelmann, V Rockova, V Teleanu, ... Journal of clinical oncology 31 (1), 95-103, 2013 | 128 | 2013 |
| Posterior concentration for sparse deep learning NG Polson, V Ročková Advances in neural information processing systems 31, 2018 | 113 | 2018 |
| Simultaneous variable and covariance selection with the multivariate spike-and-slab lasso SK Deshpande, V Ročková, EI George Journal of Computational and Graphical Statistics 28 (4), 921-931, 2019 | 89 | 2019 |
| On theory for BART V Ročková, E Saha The 22nd international conference on artificial intelligence and statistics …, 2019 | 83 | 2019 |
| The prognostic relevance of miR-212 expression with survival in cytogenetically and molecularly heterogeneous AML SM Sun, V Rockova, L Bullinger, MK Dijkstra, H Döhner, B Löwenberg, ... Leukemia 27 (1), 100-106, 2013 | 70 | 2013 |
| The median probability model and correlated variables MM Barbieri, JO Berger, EI George, V Ročková Bayesian Analysis 16 (4), 1085-1112, 2021 | 60 | 2021 |
| Dynamic variable selection with spike-and-slab process priors V Rockova, K McAlinn | 59 | 2021 |
| 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 | 56 | 2021 |
| Variance prior forms for high-dimensional Bayesian variable selection GE Moran, V Ročková, EI George | 51* | 2019 |
| Uncertainty quantification for sparse deep learning Y Wang, V Rocková International Conference on Artificial Intelligence and Statistics, 298-308, 2020 | 44 | 2020 |
| Incorporating grouping information in Bayesian variable selection with applications in genomics V Rockova, E Lesaffre | 44 | 2014 |
| Mortality rate estimation and standardization for public reporting: Medicare’s hospital compare EI George, V Ročková, PR Rosenbaum, VA Satopää, JH Silber Journal of the American Statistical Association 112 (519), 933-947, 2017 | 42 | 2017 |
| Bayesian bootstrap spike-and-slab lasso L Nie, V Ročková Journal of the American Statistical Association 118 (543), 2013-2028, 2023 | 39 | 2023 |
