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2019
Dendievel, S., Hautphenne S., Latouche G., & Taylor P. (2019).  The time-dependent expected reward and deviation matrix of a finite QBD process. Linear Algebra and its Applications. 570, 61 - 92.
Lambert, V.., Adams M.. P., Collier C.., Carter A.., Saunders M.., Brodie J.., et al. (2019).  Towards Ecologically Relevant Targets: Impact of flow and sediment discharge on seagrass communities in the Great Barrier Reef. 23rd International Congress on Modelling and Simulation (MODSIM).
Fu, J., Nazarathy Y., Moka S.. B., & Taylor P. (2019).  Towards Q-learning the Whittle Index for Restless Bandits. 2019 Australian & New Zealand Control Conference (ANZCC). 249-254.
Zhang, X., Wen F., & De Gier J. (2019).  T-Q relations for the integrable two-species asymmetric simple exclusion process with open boundaries. Journal of Statistical Mechanics: Theory and Experiment. 2019(1), 014001.
Rutter, L., Carrillo-Tripp J., Bonning B. C., Cook D., Toth A. L., & Dolezal A. G. (2019).  Transcriptomic responses to diet quality and viral infection in Apis mellifera. BMC Genomics. 20(1), 412.
Hyndman, R. J., O'Hara-Wild M., & Wang E. (2019).  tsibbledata: Diverse Datasets for 'tsibble'.
Lawson, B. A. J., Santos R. W. dos, & Turner I. (2019).  Two-dimensional monodomain solver.
Kumar, A., & Anjomshoa H. (2019).  A Two-Stage Model to Predict Surgical Patients' Lengths of Stay from an Electronic Patient Database. IEEE Journal of Biomedical and Health Informatics. 23(2), 848-856.
Salomone, R., South L. F., Drovandi C. C., & Kroese D. (2019).  Unbiased and Consistent Nested Sampling via Sequential Monte Carlo. The 12th International Conference on Monte Carlo Methods and Applications.
Moka, S. Babu, Kroese D., & Juneja S. (2019).  Unbiased Estimation of the Reciprocal Mean for Non-negative Random Variables. The 20th INFORMS Applied Probability Society Conference.
Moka, S. Babu, Kroese D., & Juneja S. (2019).  Unbiased Estimation of The Reciprocal Mean For Non-Negative Random Variables. 2019 Winter Simulation Conference (WSC). 404 - 415.
Moka, S. Babu, Kroese D., & Juneja S. (2019).  Unbiased Estimation of the Reciprocal Mean for Non-negative Random Variables with Applications. The 12th International Conference on Monte Carlo Methods and Applications.
Zhang, L., & Thompson R. G. (2019).  Understanding the benefits and limitations of occupancy information systems for couriers. Transportation Research Part C: Emerging Technologies. 105, 520 - 535.
Creutzig, T., Liu T., Ridout D., & Wood S. (2019).  Unitary and non-unitary N = 2 minimal models. Journal of High Energy Physics. 2019(6), 024.
Chen, X., Yang W., Zhang X., & Liu F. (2019).  Unsteady boundary layer flow of viscoelastic MHD fluid with a double fractional Maxwell model. Applied Mathematics Letters. 95, 143-149.
Shi, Y.., Liu F.., Zhao Y., Wang F.., & Turner I. (2019).  An unstructured mesh finite element method for solving the multi-term time fractional and Riesz space distributed-order wave equation on an irregular convex domain. Applied Mathematical Modelling. 73, 615-636.
Liu, F.., Feng L.., Anh V., & Li J. (2019).  Unstructured-mesh Galerkin finite element method for the two-dimensional multi-term time-space fractional Bloch-Torrey equations on irregular convex domains. Computers & Mathematics with Applications. 78(5), 1637-1650.
Cui, T., Fox C.., Nicholls G.. K., & O'Sullivan M.. J. (2019).  USING PARALLEL MARKOV CHAIN MONTE CARLO TO QUANTIFY UNCERTAINTIES IN GEOTHERMAL RESERVOIR CALIBRATION. International Journal for Uncertainty Quantification. 9(3), 295 - 310.
Leigh, C., Heron G., Wilson E., Gregory T., Clifford S., Holloway J., et al. (2019).  Using virtual reality and thermal imagery to improve statistical modelling of vulnerable and protected species. PLOS ONE. 14(12), e0217809.
Liquet, B. (2019).  Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set.. Seminar at the School of Mathematics and Statistics, UNSW Sydney.
Liquet, B. (2019).  Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set.. Seminar at the Department of Statistics, The University of Auckland.
Xu, M.., Quiroz M., Kohn R., & Sisson S. (2019).  Variance reduction properties of the reparameterisation trick. (Chaudhuri, K., & Sugiyama M., Ed.).The 22nd International Conference on Artificial Intelligence and Statistics. 89, 2711-2720.
Loaiza-Maya, R., & Smith M. Stanley (2019).  Variational Bayes Estimation of Discrete-Margined Copula Models With Application to Time Series. Journal of Computational and Graphical Statistics. 28(3), 523 - 539.
Loaiza-Maya, R., & Smith M. Stanley (2019).  Variational Bayes Estimation of Time Series Copulas for Multivariate Ordinal and Mixed Data.
McLean, M.. W., & Wand M. (2019).  Variational Message Passing for Elaborate Response Regression Models. Bayesian Analysis. 14(2), 371 - 398.
Wand, M. (2019).  Variational Message Passing for Elaborate Response Regression Models. AutoStat Research Week: Frontiers in Research & Practice in Statistics.
Wand, M. (2019).  Variational Message Passing for Elaborate Response Regression Models. Joint Statistical Meetings 2019.
Hamza, A., Ranathunga D., Gharakheili H. Habibi, Benson T. A., Roughan M., & Sivaraman V. (2019).  Verifying and Monitoring IoTs Network Behavior using MUD Profiles. arXiv. arXiv:1902.02484v1.
Mengersen, KL. (2019).  Virtual reality meets data science. OzViz 2019.
Peterson, E., Mengersen KL., Vercelloni J., & Brown R. (2019).  Virtual Reef Diver. International Workshop on Spatial Statistics.
Filonik, D., Rittenbruch M., Foth M., & Bednarz T. (2019).  Visualisation Design as Language Transformations - From Conceptual Models to Graphics Grammars. 2019 23rd International Conference in Information Visualization – Part II2019 23rd International Conference in Information Visualization – Part II. 18 - 23.
Rutter, L., Lauter A. N. Moran, Graham M. A., & Cook D. (2019).  Visualization methods for differential expression analysis. BMC Bioinformatics. 20(1), 458.
Cook, D., & Hofmann H. (2019).  Visualization of Big Biomedical Data. SISBID '19.
Cook, D. (2019).  Visualization of Data. useR! 2019.
O'Hara-Wild, M., Hyndman R. J., & Xie Y. (2019).  vitae: Curriculum Vitae for R Markdown.
Forrester, P. (2019).  Volumes for $${\mathrm{SL}}_N({\mathbb {R}})$$ SL N ( R ) , the Selberg Integral and Random Lattices. Foundations of Computational Mathematics. 19(1), 55 - 82.
Wand, M., & Yu J.F.C.. (2019).  Wand, M.P. and Yu, J.F.C. (2019). glmmEP 1.0. Generalized linear mixed model analysis via expectation propagation. R package. https://CRAN.R-project.org/package=glmmEP.
M. MacNeil, A., Mellin C., Matthews S., Wolff N. H., McClanahan T. R., Devlin M., et al. (2019).  Water quality mediates resilience on the Great Barrier Reef. Nature Ecology & Evolution. 3(4), 620 - 627.
Mengersen, KL. (2019).  Which way should I cycle? A case study in Bayesian modelling for decision-making under uncertainty study. ICSMTR2019: 3rd International Conference on Statistics, Mathematics, Teaching, and Research.
MacNamara, S., McLean W., & Burrage K. (2019).  Wider contours and adaptive contours. (Wood, D., De Gier J., Praeger C. E., & Tao T., Ed.).2017 MATRIX Annals. 2, 79-98.
Bean, N. G., O'Reilly M. M., & Palmowski Z. (2019).  Yaglom limit for Stochastic Fluid Models. arXiv. arXiv:1908.10827v1 .
2018
Conway, A. R., Guttmann A. J., & Zinn-Justin P. (2018).  1324-avoiding permutations revisited. Advances in Applied Mathematics. 96, 312 - 333.
[Anonymous] (2018).  2016 MATRIX Annals. (De Gier, J., Praeger C. E., Wood D. R., & Tao T., Ed.).MATRIX Book Series. 1, 656.
Qin, S., Liu F., & Turner I. (2018).  A 2D multi-term time and space fractional Bloch-Torrey model based on bilinear rectangular finite elements. Communications in Nonlinear Science and Numerical Simulation. 56, 270 -286.
[Anonymous] (2018).  The The 2nd International Conference on Econometrics and Statistics (EcoSta 2018).
Drovandi, C. C. (2018).  ABC and Indirect Inference. Handbook of Approximate Bayesian Computation. 179-210.
Fan, Y., Meikle S.. R., Angelis G.., & Sitek A.. (2018).  ABC in Nuclear Imaging. Handbook of Approximate Bayesian Computation. 623-648.
Lee, X. Ju, Hainy M., McKeone J. P., Drovandi C. C., & Pettitt A. N. (2018).  ABC model selection for spatial extremes models applied to South Australian maximum temperature data. Computational Statistics & Data Analysis. 128, 128 - 144.
Sisson, S., & Fan Y. (2018).  ABC Samplers. Handbook of Approximate Bayesian Computation. 87-124.
Acosta, M. Munoz, Hyndman R. J., & Smith-Miles K. (2018).  About outlier detection. AustMS 2018.

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