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2018
Wu, P., M. Caley J., Kendrick G. A., McMahon K., & Mengersen KL. (2018).  Dynamic Bayesian network inferencing for non-homogeneous complex systems. Journal of the Royal Statistical Society: Series C (Applied Statistics). 67(2), 417-434.
Cook, D., Laa U., & Valencia G. (2018).  Dynamical projections for the visualization of PDFSense data. The European Physical Journal C. 78(9), 
Bischel, M., Barbour A.. D., & Wagner A. (2018).  The dynamics of an insertion sequence infection in a spatially structured environment. Journal of Biological Systems. 26(1), 133-166.
Feutrill, A., Ranathunga D., Yarom Y., & Roughan M. (2018).  The Effect of Common Vulnerability Scoring System Metrics on Vulnerability Exploit Delay. 2018 Sixth International Symposium on Computing and Networking (CANDAR) . 1-10.
Obie, H.O.., Chua C., Avazpour I., Abdelrazek M., Grundy J., & Bednarz T. (2018).  The Effect of Narration on User Comprehension and Recall of Information Visualisations. OzViz 2018.
Cespedes, M. I., McGree J., Drovandi C. C., Mengersen KL., Doecke J. D., Fripp J., et al. (2018).  An efficient algorithm for estimating brain covariance networks. PLOS ONE. 13(7), e0198583.
Hassard, P., Turner I., Farrell T., & Lester D. (2018).  An efficient boundary element formulation for doubly-periodic two-dimensional Stokes flow with pressure boundary conditions. Journal of Computational Physics. 365, 18 - 36.
Chin, V.., Gunawan D.., Kohn R., & Sisson S. (2018).  Efficient data augmentation for multivariate probit models with panel data: An application to general practitioner decision-making about contraceptives.
Kang, Y., Hyndman R. J., & Li F. (2018).  Efficient generation of time series with diverse and controllable characteristics.
Andersen, L. Nørvang, Laub P., & Rojas-Nandayapa L. (2018).  Efficient Simulation for Dependent Rare Events with Applications to Extremes. Methodology and Computing in Applied Probability. 20(1), 385-409.
Gunawan, D.., Carter C.., & Kohn R. (2018).  Efficiently combining Pseudo Marginal and Particle Gibbs sampling.
Gunawan, D.., Carter C.., & Kohn R. (2018).  Efficiently combining Pseudo Marginal and Particle Gibbs sampling. Joint Statistical Meeting 2018.
Wei, S., & Panaretos V. M. (2018).  Empirical evolution equations. Electronic Journal of Statistics. 12(1), 249 - 276.
Fernandes, S., Mazumdar A., Bhattacharya S., Peketi A., Mapder T.., Roy R., et al. (2018).  Enhanced carbon-sulfur cycling in the sediments of Arabian Sea oxygen minimum zone center. Scientific Reports. 8(1), 8665.
Hossny, A. Hany, Moschuo T., Osborne G., Mitchell L., & Lothian N. (2018).  Enhancing keyword correlation for event detection in social networks using SVD and k-means: Twitter case study. Social Network Analysis and Mining. 8(1), 49.
Jony, I., Woodley A., Perrin D., & Raj A. (2018).  Ensemble Classification Technique for Water Detection in Satellite Images. International Conference on Digital Image Computing: Techniques and Applications.
Bednarz, T. (2018).  EPICentre 2018 update. OzViz 2018.
Donovan, D., Burrage K., Burrage P., McCourt TA., Thompson B., & Yazici EŞ. (2018).  Estimates of the coverage of parameter space by Latin Hypercube and Orthogonal Array-based sampling. Applied Mathematical Modelling. 57, 553-564.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Fourth Conference of the International Society for Nonparametric Statistics.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Conference on Statistical Learning and Data Science/Nonparametric Statistics.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Statistics Seminar.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Joint 2018 IMS Annual Meeting/12th International Vilnius Conference on Probability Theory and Mathematical Statistics.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Future challenges in statistical scalability workshop at ``Statistical scalability'' Programme, Newton Institute.
Delaigle, A., Hall P., Huang W., & Kneip A. (2018).  Estimating a covariance function from fragments of functional data. Meeting the Statistical Challenges in High Dimensional Data and Complex Networks workshop, Institute for Mathematical Sciences, Singapore.
Rebuli, N. P., Bean N. G., & Ross J.V. (2018).  Estimating the basic reproductive number during the early stages of an emerging epidemic. Theoretical Population Biology. 119, 26-36.
Huggins, R., Stoklosa J., Roach C., & Yip P. (2018).  Estimating the size of an open population using sparse capture–recapture data. Biometrics. 74(1), 280–288.
Kiriliouk, A., Segers J., & Tafakori L. (2018).  An estimator of the stable tail dependence function based on the empirical beta copula. Extremes. 21(4), 581 - 600.
Peirce, E.. J., McLennan H.. J., Tuke J.., Leigh C.. M., & Breed W.. G. (2018).  Evolution of the testis and spermatozoon in mice and rats (Subfamily Murinae ) in the absence of sperm competition. Journal of Zoology. 306(1), 58 - 68.
Kuhn, J., Mandjes M., & Taimre T. (2018).  Exact asymptotics of sample-mean-related rare-event probabilities. Probability in the Engineering and Informational Sciences. 32(2), 207-228.
Chen, Z., De Gier J., Hiki I., & Sasamoto T. (2018).  Exact Confirmation of 1D Nonlinear Fluctuating Hydrodynamics for a Two-Species Exclusion Process. Physical Review Letters. 120(24), 240601.
Botev, Z., Chen Y-L., LrEcuyer P., MacNamara S., & Kroese D. (2018).  Exact posterior simulation from the linear lasso regression. 2018 Winter Simulation Conference (WSC)2018 Winter Simulation Conference (WSC). 1706 - 1717.
Tsuchida, R., Roosta-Khorasani F., & Gallagher M. (2018).  Exchangeability and Kernel Invariance in Trained MLPs. arXiv preprint arXiv:1810.08351.
Kim, A. S. I., & Wand M. (2018).  On expectation propagation for generalised, linear and mixed models. Australian & New Zealand Journal of Statistics. 60(1), 75 - 102.
Petropoulos, F., Hyndman R. J., & Bergmeir C. (2018).  Exploring the sources of uncertainty: Why does bagging for time series forecasting work?. European Journal of Operational Research. 268(2), 545 - 554.
Roach, C. (2018).  Exploring unusual sensor behaviour in buildings using BMS data and unsupervised learning techniques.
Leigh, C., Aspin T. W. H., Matthews T. J., Rolls R. J., & Ledger M. E. (2018).  Extreme drought alters the temporal beta diversity and functional stability of stream invertebrate communities. Australian Freshwater Sciences Society Conference 2018.
Chen, S.., Liu F., Turner I., & Anh V.. (2018).  A fast numerical method for two-dimensional Riesz space fractional diffusion equations on a convex bounded region. Applied Numerical Mathematics. 134, 66 - 80.
Hargrave, C., Deegan T., Poulsen M., Bednarz T., Harden F., & Mengersen KL. (2018).  A feature alignment score for online cone‐beam. Medical Physics. 45(7), 2898 - 2911.
Hyndman, R. J. (2018).  Feature-based time series analysis. Workshop: International workshop on High-Dimensional Time Series and Panel Data.
Montero-Manso, P., Athanasopoulos G., Hyndman R. J., & Talagala T. (2018).  FFORMA: Feature-based Forecast Model Averaging.
Tierney, N. (2018).  Find the best locations for facilities using maxcovr. UseR 2018.
Redman, A. L., Bailleres H., Gilbert B. P., Carr E. J., Turner I., & Perré P. (2018).  Finite element analysis of stress-related degrade during drying of Corymbia citriodora and Eucalyptus obliqua. Wood Science and Technology. 52(1), 67 - 89.
L Nandayapa, R., & Bladt M. (2018).  Fitting phase–type scale mixtures to heavy–tailed data and distributions. Extremes. 21(2), 285-313.
Cheng, X., Roosta-Khorasani F., Palombo S., Bartlett P.L., & Mahoney M. (2018).  FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods. (Storkey, A., & Perez-Cruz F., Ed.).Conference on Artificial Intelligence and Statistics. 84, 404–414.
Gunawan, D.., Kohn R., Carter C.., & Tran M.. N. (2018).  Flexible density tempering approaches for state space models with an application to factor stochastic volatility models.
Tafakori, L., Pourkhanali A., & Fard F. Alavi (2018).  Forecasting spikes in electricity return innovations. Energy. 150, 508 - 526.
Manner, H., Fard F. Alavi, Pourkhanali A., & Tafakori L. (2018).  Forecasting the Joint Distribution of Australian Electricity Prices using Dynamic Vine Copulae. Energy Economics.
Leigh, C., Alsibai O., Hyndman R. J., Kandanaarachchi S., King O. C., McGree J., et al. (2018).  A framework for automated anomaly detection in high frequency water-quality data from in situ sensors. arXiv preprints.
Khaled, M. A., Makdissi P., Tabri R. V., & Yazbeck M. (2018).  A framework for testing the equality between the health concentration curve and the 45-degree line. Health Economics. 27(5), 887 - 896.
Agnew, G., Grier A., Taimre T., Bertling K., Lim Y. Leng, Ikonic Z., et al. (2018).  Frequency Tuning Range Control in Pulsed Terahertz Quantum-Cascade Lasers: Applications in Interferometry. IEEE Journal of Quantum Electronics. 54(2), 1 - 8.

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