| Speeding up MCMC by efficient data subsampling M Quiroz, M Villani, R Kohn, MN Tran Journal of the American Statistical Association, 2018 | 248 | 2018 |
| Bayesian Adaptive Lasso C Leng, MN Tran, D Nott Annals of the Institute of Statistical Mathematics, 2014 | 179 | 2014 |
| Variational Bayes with intractable likelihood MN Tran, DJ Nott, R Kohn Journal of Computational and Graphical Statistics 26 (4), 873-882, 2017 | 118 | 2017 |
| Central limit theorem for functional of jump Markov processes VH Nguyen, QH Vuong, MN Tran Springer, 2005 | 96 | 2005 |
| Bayesian Deep Net GLM and GLMM MN Tran, N Nguyen, D Nott, R Kohn Journal of Computational and Graphical Statistics, 2019 | 93 | 2019 |
| Variational Bayes with Synthetic Likelihood VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi Statistics and Computing, 2017 | 69 | 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 | 60 | 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 | 57* | 2016 |
| Hamiltonian Monte Carlo with energy conserving subsampling KD Dang, M Quiroz, R Kohn, MN Tran, M Villani Journal of Machine Learning Research, 2017 | 54 | 2017 |
| Importance sampling squared for Bayesian inference in latent variable models MN Tran, M Scharth, MK Pitt, R Kohn Behavior Research Methods, 2013 | 54 | 2013 |
| Speeding up MCMC by delayed acceptance and data subsampling M Quiroz, MN Tran, M Villani, R Kohn Journal of Computational and Graphical Statistics, 2017 | 49 | 2017 |
| A practical tutorial on Variational Bayes MN Tran | 44 | 2020 |
| 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 | 40 | 2018 |
| Subsampling MCMC-an introduction for the survey statistician M Quiroz, M Villani, R Kohn, MN Tran, KD Dang Sankhya A 80, 33-69, 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 | 31 | 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 | 30 | 2018 |
| The block pseudo-marginal sampler MN Tran, R Kohn, M Quiroz, M Villani arXiv preprint arXiv:1603.02485, 2016 | 30 | 2016 |
| New estimation approaches for the linear ballistic accumulator model D Gunawan, S Brown, R Kohn, MN Tran Journal of Mathematical Psychology, 2018 | 29* | 2018 |
| Block-wise pseudo-marginal Metropolis-Hastings MN Tran, R Kohn, M Quiroz, M Villani | 28 | 2016 |
| A statistical recurrent stochastic volatility model for stock markets TN Nguyen, MN Tran, D Gunawan, R Kohn Journal of Business & Economic Statistics 41 (2), 414-428, 2023 | 27* | 2023 |
robert kohnProfessor of Economics University of New South Wales在 unsw.edu.au 的电子邮件经过验证
