| 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 30 (4), 877-888, 2021 | 59* | 2021 |
| Hamiltonian Monte Carlo with energy conserving subsampling KD Dang, M Quiroz, R Kohn, MN Tran, M Villani Journal of machine learning research 20 (100), 1-31, 2019 | 56 | 2019 |
| Subsampling sequential Monte Carlo for static Bayesian models D Gunawan, KD Dang, M Quiroz, R Kohn, MN Tran Statistics and Computing 30 (6), 1741-1758, 2020 | 32 | 2020 |
| Subsampling MCMC-An introduction for the survey statistician M Quiroz, M Villani, R Kohn, MN Tran, KD Dang Sankhya A 80 (1), 33-69, 2018 | 29 | 2018 |
| An analysis of the spatial association between deforestation and agricultural field sizes in the tropics and subtropics DKD Dang, AC Patterson, LR Carrasco PloS One 14 (1), e0209918, 2019 | 25 | 2019 |
| Fitting structural equation models via variational approximations KD Dang, L Maestrini Structural Equation Modeling: A Multidisciplinary Journal, 1-15, 2022 | 11 | 2022 |
| Use of generalized propensity scores for assessing effects of multiple exposures K Li, T Akkaya-Hocagil, RJ Cook, LM Ryan, RC Carter, KD Dang, ... Statistics in Biosciences 16 (2), 347-376, 2024 | 3 | 2024 |
| A dose–response analysis of the effects of prenatal alcohol exposure on cognitive development JL Jacobson, T Akkaya‐Hocagil, SW Jacobson, CD Coles, ... Alcohol: Clinical and Experimental Research 48 (4), 623-639, 2024 | 3 | 2024 |
| Subsampling MCMC-A review for the survey statistician M Quiroz, M Villani, R Kohn, MN Tran, KD Dang arXiv preprint arXiv:1807.08409, 2018 | 3 | 2018 |
| Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts KD Dang, LM Ryan, T Akkaya Hocagil, RJ Cook, GA Richardson, NL Day, ... Australian & New Zealand Journal of Statistics 65 (3), 167-186, 2023 | 2 | 2023 |
| Bayesian outcome selection modelling KD Dang, LM Ryan, RJ Cook, T Akkaya‐Hocagil, SW Jacobson, ... Stat, e568, 2023 | 2 | 2023 |
| Benchmark dose profiles for bivariate exposures T Akkaya Hocagil, LM Ryan, RJ Cook, KD Dang, RC Carter, ... Risk Analysis 44 (10), 2415-2428, 2024 | 1 | 2024 |
| Simultaneous coefficient clustering and sparsity for multivariate mixed models FKC Hui, KD Dang, L Maestrini Journal of Computational and Graphical Statistics, 1-20, 2024 | 1 | 2024 |
| Bayesian structural equation modeling for data from multiple cohorts KD Dang, LM Ryan, T Akkaya-Hocagil, RJ Cook, GA Richardson, NL Day, ... arXiv preprint arXiv:2012.12085, 2020 | 1 | 2020 |
| Variational Bayes for Mixture of Gaussian Structural Equation Models KD Dang, L Maestrini, FKC Hui arXiv preprint arXiv:2407.08140, 2024 | | 2024 |
| Mixtures of Gaussian process experts based on kernel stick-breaking processes Y Saikai, KD Dang arXiv preprint arXiv:2304.13833, 2023 | | 2023 |
| Efficient Hamiltonian Monte Carlo for large data sets by data subsampling DKD Dang Journal and Proceedings of the Royal Society of New South Wales 152 (473/474 …, 2019 | | 2019 |
| Subsampling sequential Monte Carlo for static Bayesian models D Gunawan, KD Dang, M Quiroz, R Kohn, MN Tran arXiv preprint arXiv:1805.03317, 2018 | | 2018 |
