| Dirichlet–Laplace priors for optimal shrinkage A Bhattacharya, D Pati, NS Pillai, DB Dunson Journal of the American Statistical Association 110 (512), 1479-1490, 2015 | 489 | 2015 |
| Lack of confidence in approximate Bayesian computation model choice CP Robert, JM Cornuet, JM Marin, NS Pillai Proceedings of the National Academy of Sciences 108 (37), 15112-15117, 2011 | 420 | 2011 |
| Optimal tuning of the hybrid Monte Carlo algorithm A Beskos, N Pillai, G Roberts, JM Sanz-Serna, A Stuart | 370 | 2013 |
| Bayesian density regression DB Dunson, N Pillai, JH Park Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2007 | 326 | 2007 |
| Universality of covariance matrices NS Pillai, J Yin | 170 | 2014 |
| Relevant statistics for Bayesian model choice JM Marin, NS Pillai, CP Robert, J Rousseau Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2014 | 162 | 2014 |
| Combined influence of soil moisture and atmospheric evaporative demand is important for accurately predicting US maize yields AJ Rigden, ND Mueller, NM Holbrook, N Pillai, P Huybers Nature Food 1 (2), 127-133, 2020 | 148 | 2020 |
| Diffusion limits of the random walk Metropolis algorithm in high dimensions JC Mattingly, NS Pillai, AM Stuart | 127 | 2012 |
| Accelerating asymptotically exact MCMC for computationally intensive models via local approximations PR Conrad, YM Marzouk, NS Pillai, A Smith Journal of the American Statistical Association 111 (516), 1591-1607, 2016 | 121 | 2016 |
| Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions NS Pillai, AM Stuart, AH Thiéry | 121 | 2012 |
| Posterior contraction in sparse Bayesian factor models for massive covariance matrices D Pati, A Bhattacharya, NS Pillai, D Dunson | 119 | 2014 |
| Causal Inference from 2K Factorial Designs by Using Potential Outcomes T Dasgupta, NS Pillai, DB Rubin Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2015 | 94 | 2015 |
| Bayesian nonparametric weighted sampling inference Y Si, NS Pillai, A Gelman | 90 | 2015 |
| Regularity of laws and ergodicity of hypoelliptic SDEs driven by rough paths M Hairer, NS Pillai | 90 | 2013 |
| Characterizing the Function Space for Bayesian Kernel Models. NS Pillai, Q Wu, F Liang, S Mukherjee, RL Wolpert Journal of Machine Learning Research 8 (8), 2007 | 84 | 2007 |
| MCMC for imbalanced categorical data JE Johndrow, A Smith, N Pillai, DB Dunson Journal of the American Statistical Association, 2018 | 74 | 2018 |
| Ergodicity of hypoelliptic SDEs driven by fractional Brownian motion M Hairer, NS Pillai Annales de l'IHP Probabilités et statistiques 47 (2), 601-628, 2011 | 70 | 2011 |
| Bayesian shrinkage A Bhattacharya, D Pati, NS Pillai, DB Dunson arXiv preprint arXiv:1212.6088, 2012 | 64 | 2012 |
| Model comparison and assessment for single particle tracking in biological fluids M Lysy, NS Pillai, DB Hill, MG Forest, JWR Mellnik, PA Vasquez, ... Journal of the American Statistical Association 111 (516), 1413-1426, 2016 | 58 | 2016 |
| Statistical inference for dynamical systems: A review K McGoff, S Mukherjee, N Pillai | 57 | 2015 |
