| Speeding up MCMC by efficient data subsampling M Quiroz, M Villani, R Kohn, MN Tran Journal of the American Statistical Association, 2018 | 148 | 2018 |
| Bayesian Adaptive Lasso C Leng, MN Tran, D Nott Annals of the Institute of Statistical Mathematics, 2014 | 112 | 2014 |
| Variational Bayes with intractable likelihood MN Tran, DJ Nott, R Kohn Journal of Computational and Graphical Statistics 26 (4), 873-882, 2017 | 75 | 2017 |
| Variational Bayes with Synthetic Likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Statistics and Computing, 2017 | 53 | 2017 |
| The structural features and the deliberative quality of online discussions W Zhang, X Cao, MN Tran Telematics and informatics 30 (2), 74-86, 2013 | 45 | 2013 |
| Importance sampling squared for Bayesian inference in latent variable models MN Tran, M Scharth, MK Pitt, R Kohn arXiv:1309.3339, 2013 | 40 | 2013 |
| The block-Poisson estimator for optimally tuned exact subsampling MCMC M Quiroz, MN Tran, M Villani, R Kohn, KD Dang Journal of Computational and Graphical Statistics, 2016 | 37* | 2016 |
| Speeding up MCMC by delayed acceptance and data subsampling M Quiroz, MN Tran, M Villani, R Kohn Journal of Computational and Graphical Statistics, 2017 | 29 | 2017 |
| Hamiltonian Monte Carlo with energy conserving subsampling KD Dang, M Quiroz, R Kohn, MN Tran, M Villani Journal of Machine Learning Research, 2017 | 26 | 2017 |
| Likelihood-free inference in high dimensions with synthetic likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Computational Statistics & Data Analysis 128, 271-291, 2018 | 24 | 2018 |
| Bayesian Deep Net GLM and GLMM MN Tran, N Nguyen, D Nott, R Kohn Journal of Computational and Graphical Statistics, 2019 | 22 | 2019 |
| Block-wise pseudo-marginal Metropolis-Hastings MN Tran, R Kohn, M Quiroz, M Villani | 20 | 2016 |
| Central limit theorem for functional of jump Markov processes VH Nguyen, QH Vuong, MN Tran Springer, 2005 | 20 | 2005 |
| The block pseudo-marginal sampler MN Tran, R Kohn, M Quiroz, M Villani arXiv preprint arXiv:1603.02485, 2016 | 18 | 2016 |
| Simultaneous variable selection and component selection for regression density estimation with mixtures of heteroscedastic experts MN Tran, DJ Nott, R Kohn Electronic Journal of Statistics 6, 1170-1199, 2012 | 18 | 2012 |
| Variational approximation for heteroscedastic linear models and matching pursuit algorithms DJ Nott, MN Tran, C Leng Statistics and Computing 22 (2), 497-512, 2012 | 17 | 2012 |
| Penalized maximum likelihood principle for choosing ridge parameter MN Tran Communications in Statistics-Simulation and Computation 38 (8), 1610-1624, 2009 | 17 | 2009 |
| The importance of first-principles, model-based steady-state gain calculations in model predictive control—a refinery case study M Tran, DK Varvarezos, M Nasir Control Engineering Practice 13 (11), 1369-1382, 2005 | 17 | 2005 |
| Improving the efficiency of fully Bayesian optimal design of experiments using randomised quasi-Monte Carlo CC Drovandi, MN Tran Bayesian Analysis 13 (1), 139-162, 2018 | 16 | 2018 |
| The predictive lasso MN Tran, DJ Nott, C Leng Statistics and Computing 22 (5), 1069-1084, 2012 | 16 | 2012 |
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
