Minh-Ngoc Tran
Minh-Ngoc Tran
Senior Lecturer, University of Sydney
Verified email at sydney.edu.au - Homepage
Title
Cited by
Cited by
Year
Speeding up MCMC by efficient data subsampling
M Quiroz, M Villani, R Kohn, MN Tran
Journal of the American Statistical Association, 2018
1132018
Bayesian Adaptive Lasso
C Leng, MN Tran, D Nott
Annals of the Institute of Statistical Mathematics, 2014
992014
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
782018
Variational Bayes with intractable likelihood
MN Tran, DJ Nott, R Kohn
Journal of Computational and Graphical Statistics 26 (4), 873-882, 2017
622017
Variational Bayes with Synthetic Likelihood
VMH Ong, DJ Nott, MN Tran, SA Sisson, CC Drovandi
Statistics and Computing, 2017
422017
Importance sampling squared for Bayesian inference in latent variable models
MN Tran, M Scharth, MK Pitt, R Kohn
arXiv:1309.3339, 2013
402013
The structural features and the deliberative quality of online discussions
W Zhang, X Cao, MN Tran
Telematics and informatics 30 (2), 74-86, 2013
392013
The block-Poisson estimator for optimally tuned exact subsampling MCMC
M Quiroz, MN Tran, M Villani, R Kohn, KD Dang
arXiv preprint arXiv:1603.08232, 2016
332016
Speeding up MCMC by delayed acceptance and data subsampling
M Quiroz, MN Tran, M Villani, R Kohn
Journal of Computational and Graphical Statistics, 2017
272017
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
202018
Hamiltonian Monte Carlo with energy conserving subsampling
KD Dang, M Quiroz, R Kohn, MN Tran, M Villani
Journal of Machine Learning Research, 2017
202017
Block-wise pseudo-marginal Metropolis-Hastings
MN Tran, R Kohn, M Quiroz, M Villani
192016
Central limit theorem for functional of jump Markov processes
VH Nguyen, QH Vuong, MN Tran
Springer, 2005
182005
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
172012
Variational approximation for heteroscedastic linear models and matching pursuit algorithms
DJ Nott, MN Tran, C Leng
Statistics and Computing 22 (2), 497-512, 2012
162012
Penalized maximum likelihood principle for choosing ridge parameter
MN Tran
Communications in Statistics-Simulation and Computation 38 (8), 1610-1624, 2009
162009
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
162005
Subsampling sequential Monte Carlo for static Bayesian models
D Gunawan, KD Dang, M Quiroz, R Kohn, MN Tran
Statistics and Computing, 1-18, 2020
152020
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
142018
The block pseudo-marginal sampler
MN Tran, R Kohn, M Quiroz, M Villani
arXiv preprint arXiv:1603.02485, 2016
132016
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