| Speeding up MCMC by efficient data subsampling M Quiroz, M Villani, R Kohn, MN Tran Journal of the American Statistical Association, 2018 | 186 | 2018 |
| Bayesian Adaptive Lasso C Leng, MN Tran, D Nott Annals of the Institute of Statistical Mathematics, 2014 | 126 | 2014 |
| Variational Bayes with intractable likelihood MN Tran, DJ Nott, R Kohn Journal of Computational and Graphical Statistics 26 (4), 873-882, 2017 | 94 | 2017 |
| Variational Bayes with Synthetic Likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Statistics and Computing, 2017 | 65 | 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 | 50 | 2013 |
| Importance sampling squared for Bayesian inference in latent variable models MN Tran, M Scharth, MK Pitt, R Kohn Behavior Research Methods, 2013 | 45 | 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 | 44* | 2016 |
| Bayesian Deep Net GLM and GLMM MN Tran, N Nguyen, D Nott, R Kohn Journal of Computational and Graphical Statistics, 2019 | 40 | 2019 |
| Hamiltonian Monte Carlo with energy conserving subsampling KD Dang, M Quiroz, R Kohn, MN Tran, M Villani Journal of Machine Learning Research, 2017 | 35 | 2017 |
| Speeding up MCMC by delayed acceptance and data subsampling M Quiroz, MN Tran, M Villani, R Kohn Journal of Computational and Graphical Statistics, 2017 | 35 | 2017 |
| Central limit theorem for functional of jump Markov processes VH Nguyen, QH Vuong, MN Tran Springer, 2005 | 32 | 2005 |
| 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 | 31 | 2018 |
| Subsampling sequential Monte Carlo for static Bayesian models D Gunawan, KD Dang, M Quiroz, R Kohn, MN Tran Statistics and Computing, 2018 | 23 | 2018 |
| 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 | 23 | 2018 |
| Block-wise pseudo-marginal Metropolis-Hastings MN Tran, R Kohn, M Quiroz, M Villani | 22 | 2016 |
| The block pseudo-marginal sampler MN Tran, R Kohn, M Quiroz, M Villani arXiv preprint arXiv:1603.02485, 2016 | 22 | 2016 |
| Phương pháp thống kê xây dựng mô hình định mức tín nhiệm khách hàng thể nhân VQ Hoàng, ĐG Hưng, NV Hữu, TM Ngọc Vietnam Journal of Mathematical Applications 4 (2), 1-16, 2006 | 19 | 2006 |
| Variational approximation for heteroscedastic linear models and matching pursuit algorithms DJ Nott, MN Tran, C Leng Statistics and Computing 22 (2), 497-512, 2012 | 18 | 2012 |
| The ensemble Kalman filter is an ABC algorithm DJ Nott, L Marshall, TM Ngoc Statistics and Computing 22 (6), 1273-1276, 2012 | 17 | 2012 |
| The predictive lasso MN Tran, DJ Nott, C Leng Statistics and Computing 22 (5), 1069-1084, 2012 | 17 | 2012 |
robert kohnProfessor of Economics University of New South WalesVerified email at unsw.edu.au
