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2021
Fu, J., Moran B., Taylor P. G., & Xing C. (2021).  Resource competition in virtual network embedding. Stochastic Models. 37(1), 231 - 263.
Smith-Miles, K., Christiansen J., & Munoz M. Andres (2021).  Revisiting where are the hard knapsack problems? via Instance Space Analysis. Computers & Operations Research. 128, 105184.
Cook, D. (2021).  The right to access, open data, open software, diagnostics and statistics as integral components of AI. Monash MDFI Meetup Nov 25 2021.
Lau, C. L., Mayfield H. J., Sinclair J. E., Brown S. J., Waller M., Enjeti A. K., et al. (2021).  Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework. Vaccine. 39(51), 7429 - 7440.
al, JJ. Allaire et, & Hyndman R. J. (2021).  rmarkdown: Dynamic Documents for R (Version 2.11).
Garbali, A., & de Gier J. (2021).  The R-Matrix of the Quantum Toroidal Algebra $$U_{q,t}(\overset{..}{gl}_1)$$ in the Fock Module. Communications in Mathematical Physics. 384(3), 1971 - 2008.
Frazier, D. T., & Drovandi C. (2021).  Robust approximate Bayesian inference with synthetic likelihood. Journal of Computational and Graphical Statistics. 30(4), 958-976.
Callens, A.., Wang Y.-G.., Fu L.., & Liquet B.. (2021).  Robust Estimation Procedure for Autoregressive Models with Heterogeneity. Environmental Modeling & Assessment. 26(3), 313 - 323.
Farquhar, M., Burrage K., & Lawson B. A. J. (2021).  Robust Graph-based Upscaling of Microscale Fibrotic Structures. Computing in Cardiology 2021. 48, 1-4.
Dissanayake, T., Fernando T., Denman S., Sridharan S., Ghaemmaghami H., & Fookes C. (2021).  A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation. IEEE Journal of Biomedical and Health Informatics. 25(6), 2162 - 2171.
Fu, L., & Wang Y-G. (2021).  Robust regression with asymmetric loss functions. Statistical Methods in Medical Research. 30(8), 1800-1815.
Tran, M.-N.., Scharth M.., Gunawan D.., Kohn R.., Brown S.. D., & Hawkins G.. E. (2021).  Robustly estimating the marginal likelihood for cognitive models via importance sampling. Behavior Research Methods. 53(3), 1148 - 1165.
Cook, D. (2021).  The Role of R and Data Visualisation in Understanding Your World. Malaysia R 2021.
Pan, J., Cai Y., Liu M., & Li Z. (2021).  Role of vascular smooth muscle cell phenotypic switching in plaque progression: A hybrid modeling study. Journal of Theoretical Biology. 526, 110794.
Haghbin, H., & Hyndman R. J. (2021).  Rsfar: Seasonal Functional Autoregressive Models.
Dandekar, R., Henderson S. G., Jansen H. M., McDonald J., Moka S., Nazarathy Y., et al. (2021).  Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics. Patterns. 2(3), 100220.
Munoz, M. Andres, & Kirley M. (2021).  Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization. Algorithms. 14(1), 19.
Lefèvre, C., & Simon M. (2021).  Schur-Constant and Related Dependence Models, with Application to Ruin Probabilities. Methodology and Computing in Applied Probability. 23(1), 317-339.
Talagala, T., Hyndman R. J., & Athanasopoulos G. (2021).  seer: Feature-Based Forecast Model Selection (Version 1.1.6).
L. F. South, Karvonen T.., Nemeth C.., Girolami M., & Oates C. J. (2021).  Semi-exact control functionals from Sard's method. Biometrika.
di Marco, V., & Keith J. (2021).  Sequential Importance Sampling With Corrections For Partially Observed States. ANZSC2021.
di Marco, V., & Keith J. M. (2021).  Sequential Importance Sampling With Corrections For Partially Observed States. arXiv. arXiv:2103.05217v1.
di Marco, V., & Keith J. (2021).  Sequential Importance Sampling With Corrections For Partially Observed States. ISBA 2021 (virtual conference).
di Marco, V., & Keith J. (2021).  Sequential Importance Sampling With Corrections For Partially Observed States. arXiv.
Vaisman, R. (2021).  Sequential stratified splitting for efficient Monte Carlo integration. Sequential Analysis. 40(3), 314 - 335.
Guttmann, T. (2021).  Series analysis applied to several combinatorial problems. Mathematical Physics Group Seminars.
Roosta, F., Hodgkinson L., van der Heide C., & Kroese D. (2021).  Shadow Manifold Hamiltonian Monte Carlo. Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. 130, 1477-1485.
Browning, R., Sulem D., Mengersen K., Rivoirard V., & Rousseau J. (2021).  Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19. PLOS ONE. 16(4), e0250015.
Browning, R. (2021).  Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19. 2021 World Meeting of the International Society for Bayesian Analysis (ISBA 2021).
Wang, L., Chen Q., Yarlagadda P. K. D. V., Zhu F., Li Q., & Li Z. (2021).  Single-parameter mechanical design of a 3D-printed octet truss topological scaffold to match natural cancellous bones. Materials & Design. 209, 109986.
Ma, Y., Mummullage S., Wijesiri B., Egodawatta P., McGree J., Ayoko G. A., et al. (2021).  Source quantification and risk assessment as a foundation for risk management of metals in urban road deposited solids. Journal of Hazardous Materials. 408, 124912.
An, X., Liu F., Zheng M., Anh V. V., & Turner I. W. (2021).  A space-time spectral method for time-fractional Black-Scholes equation. Applied Numerical Mathematics. 165, 152 - 166.
Dufays, A., Li Z., Rombouts J. V. K., & Song Y. (2021).  Sparse change‐point VAR models. Journal of Applied Econometrics. 36(6), 703-727.
Holloway-Brown, J., Helmstedt K. J., & Mengersen K. L. (2021).  Spatial Random Forest (S-RF): A random forest approach for spatially interpolating missing land-cover data with multiple classes. International Journal of Remote Sensing. 42(10), 3756 - 3776.
Pfiester, L. Mali, Thompson R. G., & Zhang L. (2021).  Spatiotemporal exploration of Melbourne pedestrian demand. Journal of Transport Geography. 95, 103151.
Duan, Q., McGrory C. A., Brown G., Mengersen K., & Wang Y-G. (2021).  Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: a study of long-term daily temperature in Australia. arXiv. arXiv:2103.05791v1.
Li, W., Cook D., & Dodwell E. (2021).  spotoroo: Spatiotemporal Clustering of Satellite Hot Spot Data.
Yang, Y., Fan X., Xu C., Wu J., & Sun B. (2021).  State Consensus Cooperative Control for a Class of Nonlinear Multi-Agent Systems with Output Constraints via ADP Approach. Neurocomputing. 458, 284-296.
VanderPlas, S., Röttger C., Cook D., & Hofmann H. (2021).  Statistical significance calculations for scenarios in visual inference. Stat. 10(1), e337.
Cook, D. (2021).  Statistics on street corners: Conducting inference for data plots. 2021 NONCLINICAL BIOSTATISTICS CONFERENCE.
Cramb, S. M., Lazzarini P., Barnett A., & Daniel M. (2021).  Stepping up: identifying small-area variation in diabetes-related lower limb amputations. World Congress of Epidemiology.
Hodgkinson, L., van der Heide C., Roosta F., & Mahoney M. (2021).  Stochastic Continuous Normalizing Flows: Training SDEs as ODEs. Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence. 161, 1130–1140.
Fackrell, M., Taylor P., & Wang J. (2021).  Strategic customer behavior in an M/M/1 feedback queue. Queueing Systems. 97(3-4), 223 - 259.
Degani, E., Maestrini L., Toczydlowska D., & Wand M. (2021).  Streamlined Variational Inference for High Dimensional Mixed Models with Fixed Effects Selection. Australian and New Zealand Statistical Conference (ANZSC 2021).
Menictas, M.., Nolan T.H.., Simpson D.G.., & Wand M. (2021).  Streamlined variational inference for higher level group-specific curve models. Statistical Modelling. 21(6), 479-519.
Wand, M. P. (2021).  Streamlined variational inference for random effects models. Computational and Financial Econometrics European Research Consortium for Informatics and Mathematics Working Group Conference 2021.
Polak, J., & Cook D. (2021).  A Study on Student Performance, Engagement, and Experience With Kaggle InClass data Challenges. Journal of Statistics and Data Science Education. 29(1), 63 - 70.
Wu, J., Wang Y-G., Tian Y-C., Burrage K., & Cao T. (2021).  Support vector regression with asymmetric loss for optimal electric load forecasting. Energy. 223, 119969.
Asanjarani, A., Nazarathy Y., & Taylor P. (2021).  A survey of parameter and state estimation in queues. Queueing Systems. 97, 39-80.
Asanjarani, A., Nazarathy Y., & Taylor P. (2021).  A survey of parameter and state estimation in queues: A tutorial. Data Driven Queueing Challenges (DDQC 2021).

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