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PUBLICATIONS FOR 2020

Year of publication
2014 2015 2016 2017 2018 2019 2020 Total
Number of publications included in citation count 20 210 138 125 131 119 122 865
Number of publications with at least one citation 19 203 131 119 117 98 59 746
Number of citations by year of citation 2014 5 3 0 0 0 0 0 8
2015 43 162 5 0 0 0 0 210
2016 48 575 108 2 0 0 0 733
2017 60 674 401 92 3 0 0 1230
2018 65 752 605 353 114 4 1 1894
2019 74 695 627 460 349 104 8 2317
2020 83 741 762 634 517 364 359 3460
Total citations by year of publication 374 3602 2508 1541 983 472 368 9852

Book

Book - authored other
  1. Duncan, E. W., Cramb, S. M., Baade, P. D., Mengersen, K. L., Saunders, T., & Aitken, J. F. (2020). Developing a Cancer Atlas using Bayesian Methods: A Practical Guide for Application and Interpretation. Brisbane: Queensland University of Technology (QUT) and Cancer Council Queensland. Read online
Book - edited
  1. Mengersen, K. L., Pudlo, P., & Robert, C. P. (Eds.) (2020). Case Studies in Applied Bayesian Data Science. Lecture Notes in Mathematics (Vol. 2259). Cham: Springer International Publishing. Read online

Book Chapters

Book chapter
  1. Aswi, A., Cramb, S., Hu, W., White, G. & Mengersen, K. L. (2020). Spatio-Temporal Analysis of Dengue Fever in Makassar Indonesia: A Comparison of Models Based on CARBayes. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 229 - 244). Cham: Springer International Publishing. Read online
  2. Bian, L., Cui, T., Sofronov, G., & Keith, J. (2020). Network Structure Change Point Detection by Posterior Predictive Discrepancy. In Tuffin, B., & L'Ecuyer, P. (Eds.), Monte Carlo and Quasi-Monte Carlo Methods. MCQMC 2018. Springer Proceedings in Mathematics & Statistics, (Vol. 324, pp. 107 - 123). Cham: Springer International Publishing. Read online
  3. Cespedes, M. I., McGree, J. M., Drovandi, C. C., Mengersen, K. L., Reid, L. B., Doecke, J. D., & Fripp, J. (2020). A Bayesian Hierarchical Approach to Jointly Model Cortical Thickness and Covariance Networks. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 155 - 213). Cham: Springer International Publishing. Read online
  4. Cramb, S., Duncan, E., Baade, P., & Mengersen, K. L. (2020). A Comparison of Bayesian Spatial Models for Cancer Incidence at a Small Area Level: Theory and Performance. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 245 - 274). Cham: Springer International Publishing. Read online
  5. Davis, G., Moloney, E., da Palma, M., Mengersen, K.L., & Harden, F. (2020). Workplace Health and Workplace Wellness: Synergistic or Disconnected? In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 303 - 326). Cham: Springer International Publishing. Read online
  6. Davis, J., Good, K., Hunter, V., Johnson, S., & Mengersen, K. L. (2020). Bayesian Networks for Understanding Human-Wildlife Conflict in Conservation. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 347 - 370). Cham: Springer International Publishing. Read online
  7. Jahan, F., Ullah, I., & Mengersen, K. L. (2020). A Survey of Bayesian Statistical Approaches for Big Data. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 17 - 44). Cham: Springer International Publishing. Read online
  8. Mengersen, K. L., Pudlo, P., & Robert, C. P. (2020). Introduction. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 3 - 15). Cham: Springer International Publishing. Read online
  9. Moores, M. T., Pettitt, A. N., & Mengersen, K. L. (2020). Bayesian Computation with Intractable Likelihoods. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 137 - 151). Cham: Springer International Publishing. Read online
  10. Santos‐Fernandez, E., Mengersen, K. L., & Wu, P. (2020). Bayesian Methods in Sport Statistics. In Balakrishnan, N., Colton, T., Everitt, B., Piegorsch, W., Ruggeri, F., & Teugels, J. (Eds.) Wiley StatsRef: Statistics Reference Online. Chichester, UK: John Wiley & Sons, Ltd. Read online
  11. Sequeira, A. M. M., M. Caley, J., Mellin, C., & Mengersen, K. L. (2020). Bayesian Learning of Biodiversity Models Using Repeated Observations. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 371 - 384). Cham: Springer International Publishing. Read online
  12. Sutton, M. (2020). Bayesian Variable Selection. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 121 - 135). Cham: Springer International Publishing. Read online
  13. Taimre, T., Kroese, D., & Botev, Z. I. (2020). Monte Carlo Methods. In Balakrishnan, N., Colton, T., Everitt, B., Piegorsch, W., Ruggeri, F., & Teugels, J. L. (Eds.), Wiley StatsRef: Statistics Reference Online. Chichester, UK: John Wiley & Sons, Ltd. Read online
  14. Thomas, A., Wu, P., White, N. M., Toms, L., Mellick, G., & Mengersen, K. L. (2020). An Ensemble Approach to Modelling the Combined Effect of Risk Factors on Age at Parkinson’s Disease Onset. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 275 - 302). Cham: Springer International Publishing. Read online
  15. Tierney, N. J., Clifford, S., Drovandi, C. C., & Mengersen, K. L. (2020). Bayesian Modelling to Assist Inference on Health Outcomes in Occupational Health Surveillance. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 327 - 343). Cham: Springer International Publishing. Read online
  16. Ullah, I., & Mengersen, K. L. (2020). Application of Bayesian Mixture Models to Satellite Images and Estimating the Risk of Fire-Ant Incursion in the Identified Geographical Cluster. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 399 - 417). Cham: Springer International Publishing. Read online
  17. Vercelloni, J., M. Caley, J., Mengersen, K. L. (2020). Thresholds of Coral Cover That Support Coral Reef Biodiversity. In Mengersen, K. L., Pudlo, P., & Robert, C. P. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 385 - 398). Cham: Springer International Publishing. Read online
  18. Weber, D., Nasim, M., Falzon, L., & Mitchell, L. (2020). #ArsonEmergency and Australia’s “Black Summer”: Polarisation and Misinformation on Social Media. In van Duijn, M., Preuss, M., Spaiser, V., Takes, F., & Verberne, S. (Eds.), Lecture Notes in Computer Science: Disinformation in Open Online Media (Vol. 12259, pp. 159 - 173). Cham: Springer International Publishing. Read online
  19. White, N., van Havre, Z., Rousseau, J., & Mengersen, K. L. (2020). Bayesian Spike Sorting: Parametric and Nonparametric Multivariate Gaussian Mixture Models. In Mengersen, K. L., Pudlo, P., & Robert, C. (Eds.), Lecture Notes in Mathematics: Case Studies in Applied Bayesian Data Science (Vol. 2259, pp. 215 - 227). Cham: Springer International Publishing. Read online
  20. Wu, J., & Ding, Z. (2020). Improved Grey Model by Dragonfly Algorithm for Chinese Tourism Demand Forecasting. Improved Grey Model by Dragonfly Algorithm for Chinese Tourism Demand Forecasting. In Fujita, H., Fournier-Viger, P., Ali, M., & Sasaki, J. (Eds.), Lecture Notes in Computer Science: Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices. (Vol. 12144, pp. 199 - 209). Cham: Springer International Publishing. Read online
  21. Xie, H. - B., Li C., Xu R. Y. D., & Mengersen, K. L. (2020). Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation. In Nicosia, G., Pardalos, P., Umeton, R., Giuffrida, G., & Sciacca, V. (Eds.), Lecture Notes in Computer Science: Machine Learning, Optimization, and Data Science (Vol. 1, pp. 484 - 495). Cham: Springer International Publishing. Read online

Journal Articles

Article in scholarly refereed journal
  1. Abera, A. K., O’Reilly, M. M., Fackrell, M., Holland, B. R., & Heydar, M. (2020). On the decision support model for the patient admission scheduling problem with random arrivals and departures: A solution approach. Stochastic Models, 36(2), 312 - 336. Read online
  2. Adams, M. P., Koh, E. J. Y., Vilas, M. P., Collier, C. J., Lambert, V. M., Sisson, S. A., Quiroz, M., McDonald-Madden, E., McKenzie, L. J., & O'Brien, K. R. (2020). Predicting seagrass decline due to cumulative stressors. Environmental Modelling & Software, 130, 104717. Read online
  3. Adams, M. P., Sisson, S., Helmstedt, K. J., Baker, C. M., Holden, M. H., Plein, M., Holloway, J., Mengersen, K. L., & McDonald-Madden, E. (2020). Informing management decisions for ecological networks, using dynamic models calibrated to noisy time‐series data. Ecology Letters, 23(4), 607-619. Read online
  4. Alahmadi, A., Belet, S., Black, A. J., Cromer, D., Flegg, J. A., House, T., Jayasundara, P., Keith, J. M., McCaw, J. M., Moss, R., Ross, J. V., Shearer, F. M., Tun, S. T. T., Walker, J., White, L., Whyte, J. M., Yan, A. W. C, Alexander E. Zarebski, A. E. (2020). Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges. Epidemics, 32, 100393. Read online
  5. Alahmadi, A. A., Flegg, J. A., Cochrane, D. G., Drovandi, C. C., & Keith, J. M. (2020). A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models. Royal Society Open Science, 7(3), 191315. Read online
  6. Alkhairy, I., Low-Choy, S., Murray, J., Wang, J., & Pettitt, A. (2020). Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat. Journal Of Applied Statistics, 47(10), 1848-1884. Read online
  7. An, Z., Nott, D. J., & Drovandi, C. (2020). Robust Bayesian synthetic likelihood via a semi-parametric approach. Statistics And Computing, 30, 543-557. Read online
  8. Asanjarani, A., & Nazarathy, Y. (2020). The Role of Information in System Stability with Partially Observable Servers. Methodology And Computing In Applied Probability, 22, 949-968. Read online
  9. Aswi, A., Cramb, S., Duncan, E., Hu, W., White, G., & Mengersen, K. L. (2020). Bayesian spatial survival models for hospitalisation of dengue: A case study of Wahidin hospital in Makassar, Indonesia. International Journal Of Environmental Research And Public Health, 17(3), 878. Read online
  10. Aswi, A., Cramb, S., Duncan, E., Hu, W., White, G., & Mengersen, K. L. (2020). Climate variability and dengue fever in Makassar, Indonesia: Bayesian spatio-temporal modelling. Spatial And Spatio-Temporal Epidemiology, 33, 100335. Read online
  11. Aswi, A., Cramb, S., Duncan, E. W., & Mengersen, K. (2020). Evaluating the impact of a small number of areas on spatial estimation. International Journal Of Health Geographics, 19(1), 39. Read online
  12. Baniasadi, P., Foumani, M., Smith-Miles, K., & Ejov, V. (2020). A transformation technique for the clustered generalized traveling salesman problem with applications to logistics. European Journal Of Operational Research, 285(2), 444 - 457. Read online
  13. Barbour, A. D., Ross, N., & Wen, Y. (2020). Central moment inequalities using Stein’s method. Electronic Journal Of Probability, 25, 91. Read online
  14. Bardsley, J. M., Cui, T., Marzouk, Y. M., & Wang, Z. (2020). Scalable Optimization-Based Sampling on Function Space. SIAM Journal On Scientific Computing, 42(2), A1317 - A1347. Read online
  15. Beaton, N. R., Guttmann, A. J., & Jensen, I. (2020). Two-dimensional interacting self-avoiding walks: new estimates for critical temperatures and exponents. Journal Of Physics A: Mathematical And Theoretical, 53(16), 165002. Read online
  16. Beavan, A., Chin, V., Ryan, L., Spielmann, J., Mayer, J., Skorski, S., & Fransen, J. (2020). A longitudinal analysis of the executive functions in high-level football players. Journal Of Sport And Exercise Psychology, 42(5), 349-357. Read online
  17. Black, A. J., Bourrat, P., & Rainey, P. B. (2020). Ecological scaffolding and the evolution of individuality. Nature Ecology & Evolution, 4(3), 426 - 436. Read online
  18. Bostan, A., Price, A. Elvey, Guttmann, A. J., & Maillard, J. - M. (2020). Stieltjes moment sequences for pattern-avoiding permutations. The Electronic Journal Of Combinatorics, 27(4), P4.20. Read online
  19. Bowden, R., Keeler, H. P., Krzesinski, A. E., & Taylor, P. G. (2020). Modeling and analysis of block arrival times in the Bitcoin blockchain. Stochastic Models, 36(4), 602-637. Read online
  20. Broc, C., Calvo, B., & Liquet, B. (2020). Penalized Partial Least Square applied to structured data. Arabian Journal Of Mathematics, 9, 329-344. Read online
  21. Brown, R. D., Bardsley, J. M., & Cui, T. (2020). Semivariogram methods for modeling Whittle–Matérn priors in Bayesian inverse problems. Inverse Problems, 36(5), 055006. Read online
  22. Browning, A. P., Jin, W., Plank, M. J., & Simpson, M. J. (2020). Identifying density-dependent interactions in collective cell behaviour. Journal Of The Royal Society Interface, 17(165), 20200143. Read online
  23. Browning, A. P., Warne, D. J., Burrage, K., Baker, R. E., & Simpson, M. J. (2020). Identifiability analysis for stochastic differential equation models in systems biology. Journal Of The Royal Society Interface, 17(173), 20200652. Read online
  24. Burrage, K., Burrage, P., Davis, J., Bednarz, T., Kim, J., Vercelloni, J., Peterson, E. E., & Mengersen, K. (2020). A stochastic model of jaguar abundance in the Peruvian Amazon under climate variation scenarios. Ecology And Evolution, 10(19), 10829 - 10850. Read online
  25. Cespedes, M. I., McGree, J. M., Drovandi, C. C., Mengersen, K. L., Fripp, J., & Doecke, J. D. (2020). Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration. Statistics In Medicine, 39(21), 2695 - 2713. Read online
  26. Chen, Z., de Gier, J., & Wheeler, M. (2020). Integrable Stochastic Dualities and the Deformed Knizhnik–Zamolodchikov Equation. International Mathematics Research Notices, 2020(19), 5872 - 5925. Read online
  27. Chin, V., Gunawan, D., Fiebig, D., Kohn, R., & Sisson, S. (2020). Efficient data augmentation for multivariate probit models with panel data: An application to general practitioner decision-making about contraceptives. Journal Of Royal Statistical Society, 69(2), 277-300. Read online
  28. Clark, S., Hyndman, R. J., Pagendam, D., & Ryan, L. M. (2020). Modern Strategies for Time Series Regression. International Statistical Review, 88(S1), s179-s204. Read online
  29. Colbrook, M. J., Botev, Z. I., Kuritz, K., & MacNamara, S. (2020). Kernel density estimation with linked boundary conditions. Studies In Applied Mathematics, 145(3), 357 - 396. Read online
  30. Collevecchio, A., Kious, D., & Sidoravicius, V. (2020). The Branching‐Ruin Number and the Critical Parameter of Once‐Reinforced Random Walk on Trees. Communications On Pure And Applied Mathematics, 73(1), 210-236. Read online
  31. Collevecchio, A., Takei, M., & Uematsu, Y. (2020). Functional central limit theorem for random walks in random environment defined on regular trees. Stochastic Processes And Their Applications, 130(8), 4892 - 4909. Read online
  32. Cope, R. C., & Ross, J. V. (2020). Identification of the relative timing of infectiousness and symptom onset for outbreak control. Journal Of Theoretical Biology, 486, 110079. Read online
  33. Crotty, S. M., Minh, B. Quang, Bean, N. G., Holland, B. R., Tuke, J., Jermiin, L. S., & Von Haeseler, A. (2020). GHOST: Recovering Historical Signal from Heterotachously Evolved Sequence Alignments. Systematic Biology, 69(2), 249-264. Read online
  34. Deelstra, G., Latouche, G., & Simon, M. (2020). On barrier option pricing by Erlangization in a regime-switching model with jumps. Journal Of Computational And Applied Mathematics, 371, 112606. Read online
  35. Delaigle, A., Huang, W., & Lei, S. (2020). Estimation of Conditional Prevalence From Group Testing Data With Missing Covariates. Journal Of The American Statistical Association, 115(529), 467-480. Read online
  36. Diao, J., Stark, T. L., Liberles, D. A., O’Reilly, M. M., & Holland, B. R. (2020). Level-dependent QBD models for the evolution of a family of gene duplicates. Stochastic Models, 36(2), 285-311. Read online
  37. Du, H., Perré, P., & Turner, I. (2020). Modelling fungal growth with fractional transport models. Communications In Nonlinear Science And Numerical Simulation, 84, 105157. Read online
  38. Duplantier, B., & Guttmann, A. J. (2020). Statistical Mechanics of Confined Polymer Networks. Journal Of Statistical Physics, 180(1-6), 1061 - 1094. Read online
  39. Dyson, F. J., Frankel, N. E., & Guttmann, A. J. (2020). SanD primes and numbers. Journal Of Integer Sequences, 23, 20.3.4. Read online
  40. Fang, S., Grimm, J., Zhou, Z., & Deng, Y. (2020). Complete graph and Gaussian fixed-point asymptotics in the five-dimensional Fortuin-Kasteleyn Ising model with periodic boundaries. Physical Review E, 102(2), 022125. Read online
  41. Feng, L., Liu, F., & Turner, I. (2020). An unstructured mesh control volume method for two- dimensional space fractional diffusion equations with variable coefficients on convex domains. Journal Of Computational And Applied Mathematics, 364, 112319. Read online
  42. Fitzgerald, S. Paul, Bean, N. G., Falhammar, H., & Tuke, J. (2020). Clinical Parameters Are More Likely to Be Associated with Thyroid Hormone Levels than with Thyrotropin Levels: A Systematic Review and Meta-Analysis. Thyroid, 30(12), 1695 - 1709. Read online
  43. Forrester, P., & Li, S. - H. (2020). Classical discrete symplectic ensembles on the linear and exponential lattice: skew orthogonal polynomials and correlation functions. Transactions Of The American Mathematical Society, 373, 665-698. Read online
  44. Foumani, M., Razeghi, A., & Smith-Miles, K. (2020). Stochastic optimization of two-machine flow shop robotic cells with controllable inspection times: From theory toward practice. Robotics And Computer-Integrated Manufacturing, 61, 101822. Read online
  45. Fu, J., & Moran, B. (2020). Energy-Efficient Job-Assignment Policy With Asymptotically Guaranteed Performance Deviation. IEEE/ACM Transactions On Networking, 28(3), 1325 - 1338. Read online
  46. Fu, L., Wang, B., Yuan, T., Chen, X., Ao, Y., Fitzpatrick, T., Li, P., Zhou, Y., Lin, Y., Duan, Q., Luo, G., Fan, S., Lu, Y., Feng, A., Zhan, Y., Liang, B., Cai, W., Zhang, L., Du, X., Li, L., Shu, Y., & Zou, H. (2020). Clinical characteristics of coronavirus disease 2019 (COVID-19) in China: A systematic review and meta-analysis. Journal Of Infection, 80(6), 656 - 665. Read online
  47. Furtwängler, A., Rohrlach, A. B., Lamnidis, T. C., Papac, L., Neumann, G. U., Siebke, I., Reiter, E., Steuri, N., Hald, J., Denaire, A., Schnitzler, B., Wahl, J., Ramstein, M., Schuenemann, V. J., Stockhammer, P. W., Hafner, A., Lösch, S., Haak, W., Schiffels, S., & Krause, J. (2020). Ancient genomes reveal social and genetic structure of Late Neolithic Switzerland. Nature Communications, 11(1), 1915. Read online
  48. Gao, S., Wu, J., Stiller, J., Zheng, Z., Zhou, M., Wang, Y. - G., & Liu, C. (2020). Identifying barley pan-genome sequence anchors using genetic mapping and machine learning. Theoretical And Applied Genetics, 133(9), 2535 - 2544. Read online
  49. Gao, X., Liu, F., Li, H., Liu, Y., Turner, I., & Yin, B. (2020). A novel finite element method for the distributed-order time fractional Cable equation in two dimensions. Computers & Mathematics With Applications, 80(5), 923 - 939. Read online
  50. Gilholm, P., Mengersen, K. L., & Thompson, H. (2020). Identifying latent subgroups of children with developmental delay using Bayesian sequential updating and Dirichlet process mixture modelling. PLOS One, 15(6), e0233542. Read online
  51. González-Rivero, M., Beijbom, O., Rodriguez-Ramirez, A., Bryant, D. E. P., Ganase, A., Gonzalez-Marrero, Y., Herrera-Reveles, A.; Kennedy, E. V., Kim, C. J. S., Lopez-Marcano, S., Markey, K., Neal, B. P., Osborne, K., Reyes-Nivia, C., Sampayo, E. M., Stolberg, K., Taylor, A., Vercelloni, J., Wyatt, M., Hoegh-Guldberg, O. (2020). Monitoring of Coral Reefs Using Artificial Intelligence: A Feasible and Cost-Effective Approach. Remote Sensing, 12(3), 489. Read online
  52. Gray, C., Mitchell, L., & Roughan, M. (2020). Bayesian Inference of Network Structure From Information Cascades. IEEE Transactions On Signal And Information Processing Over Networks, 6, 371 - 381. Read online
  53. Grazian, C., & Fan, Y. (2020). A review of Approximate Bayesian Computation methods via density estimation: inference for simulator-models. Wiley Interdisciplinary Reviews: Computational Statistics, 12(4), e1486. Read online
  54. Gunawan, D., Dang, K. - D., Quiroz, M., Kohn, R., & Tran, M. - N. (2020). Subsampling sequential Monte Carlo for static Bayesian models. Statistics And Computing, 30(6), 1741 - 1758. Read online
  55. Gunawan, D., Khaled, M. A., & Kohn, R. (2020). Mixed Marginal Copula Modeling. Journal Of Business & Economic Statistics, 38(1), 137-147. Read online
  56. Hartigan, J., MacNamara, S., & Leslie, L. M. (2020). Application of Machine Learning to Attribution and Prediction of Seasonal Precipitation and Temperature Trends in Canberra, Australia. Climate, 8(6), 76. Read online
  57. Hartigan, J., MacNamara, S., Leslie, L. M., & Speer, M. (2020). Attribution and Prediction of Precipitation and Temperature Trends within the Sydney Catchment Using Machine Learning. Climate, 8(10), 120. Read online
  58. Hayat, S., Rextin, A., Idris, A., & Nasim, M. (2020). Text and phone calls: user behaviour and dual-channel communication prediction. Human-Centric Computing And Information Sciences, 10(1), 11. Read online
  59. Hobbs, W., Wu, P. Pao- Yen, Gorman, A. D., Mooney, M., & Freeston, J. (2020). Bayesian hierarchical modelling of basketball tracking data - a case study of spatial entropy and spatial effectiveness. Journal Of Sports Sciences, 38(8), 886 - 896. Read online
  60. Hodgkinson, L., McVinish, R., & Pollett, P. (2020). Normal approximations for discrete-time occupancy processes. Stochastic Processes And Their Applications, 130(10), 6414 - 6444. Read online
  61. Holloway-Brown, J., Helmstedt, K. J., & Mengersen, K. L. (2020). Stochastic spatial random forest (SS-RF) for interpolating probabilities of missing land cover data. Journal Of Big Data, 7(1), 55. Read online
  62. Holmes, M., & Taylor, P. G. (2020). A paradox for expected hitting times. Stochastic Models, 36(3), 365 - 377. Read online
  63. Hu, S., Ingham, A., Schmoelzl, S., McNally, J., Little, B., Smith, D., Bishop-Hurley, G., Wang. Y.-G., & Li, Y. (2020). Inclusion of features derived from a mixture of time window sizes improved classification accuracy of machine learning algorithms for sheep grazing behaviours. Computers And Electronics In Agriculture, 179, 105857. Read online
  64. Hwang, H., & Ryan, L. M. (2020). Statistical strategies for the analysis of massive data sets. Biometrical Journal, 62(2), 270-281. Read online
  65. Härkönen, T., Roininen, L., Moores, M., & Vartiainen, E. M. (2020). Bayesian Quantification for Coherent Anti-Stokes Raman Scattering Spectroscopy. The Journal Of Physical Chemistry B, 124(32), 7005-7012. Read online
  66. Jahan, F., Duncan, E. W., Cramb, S., Baade, P. D., & Mengersen, K. L. (2020). Augmenting disease maps: a Bayesian meta-analysis approach. Royal Society Open Science, 7(8), 192151. Read online
  67. Jahan, F., Duncan, E. W., Cramb, S., Baade, P. D., & Mengersen, K. L. (2020). Multivariate Bayesian meta-analysis: joint modelling of multiple cancer types using summary statistics. International Journal Of Health Geographics, 19(1), 42. Read online
  68. Jin, G., Xu, J., Mo, Y., Tang, H., Wei, T., Wang, Y. - G., & Li, L. (2020). Response of sediments and phosphorus to catchment characteristics and human activities under different rainfall patterns with Bayesian Networks. Journal Of Hydrology, 584, 124695. Read online
  69. Johansen, K., Duan, Q., Tu, Y. - H., Searle, C., Wu, D., Phinn, S., Robson, A., & McCabe, M. F. (2020). Mapping the condition of macadamia tree crops using multi-spectral UAV and WorldView-3 imagery. ISPRS Journal Of Photogrammetry And Remote Sensing, 165, 28 - 40. Read online
  70. Kang, Y., Hyndman, R. J., & Li, F. (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. Statistical Analysis And Data Mining: The ASA Data Science Journal, 13(4), 354 - 376. Read online
  71. Keller, P. S., Catalán, N., von Schiller, D., Grossart, H. - P., Koschorreck, M., Obrador, B., Frassl, M. A., Karakaya, N., Barros, N., Howitt, J. A., Mendoza-Lera, C., Pastor, A., G. Flaim, G., Aben, R., T. Riis, T., Arce, M. I., G. Onandia, G., Paranaíba, J. R., Linkhorst, A., del Campo, R., Amado, A. M., Cauvy-Fraunié, S., Brothers, S., Condon, J., Mendonça, R. F., Reverey, F., Rõõm, E.-I., Datry, T., Roland, F., Laas, A., Obertegger, U., Park, J.-H.Wang, H., Kosten, S., Gómez, R., Feijoó, C., Elosegi, A., Sánchez-Montoya, M. M., Finlayson, C. M., Melita, M., Oliveira Junior, E. S., Muniz, C. C., Gómez-Gener, L., Leigh, C., Zhang, Q., & Marcé, R. (2020). Global CO2 emissions from dry inland waters share common drivers across ecosystems. Nature Communications, 11(1), 2126. Read online
  72. Kennedy, E. V., Vercelloni, J., Neal, B. P., Ambariyanto, Bryant, D. E. P., Ganase, A., Gartrell, P., Brown, K., Kim, C. J. S., Hudatwi, M., Hadi, A., Prabowo, A., Prihatinningsih, P., Haryanta, S., Markey, K., Green, S., Dalton, P., Lopez-Marcano, S., Rodriguez-Ramirez, A., Gonzalez-Rivero, M., & Hoegh-Guldberg, O. (2020). Coral Reef Community Changes in Karimunjawa National Park, Indonesia: Assessing the Efficacy of Management in the Face of Local and Global Stressors. Journal Of Marine Science And Engineering, 8(10), 760. Read online
  73. Lawson, B. A. J., Oliveira, R. S., Berg, L. A., Silva, P. A. A., Burrage, K., & Weber dos Santos, R. (2020). Variability in electrophysiological properties and conducting obstacles controls re-entry risk in heterogeneous ischaemic tissue. Philosophical Transactions Of The Royal Society A: Mathematical, Physical And Engineering Sciences, 378(2173), 20190341. Read online
  74. Lee, J. Y. L., Green, P. J., & Ryan, L. M. (2020). Analysis of grouped data using conjugate generalized linear mixed models. Biometrika, 107(1), 231-237. Read online
  75. Lefèvre, C., & Simon, M. (2020). SIR-Type Epidemic Models as Block-Structured Markov Processes. Methodology And Computing In Applied Probability, 22, 433-453. Read online
  76. Leigh, C., Stewart-Koster, B., Sang, N. V., Truc, L. V., Hiep, L. H., Xoan, V. B., Tinh, N. T. N., An, L. T., Sammut, J., & Burford, M. A. (2020). Rice-shrimp ecosystems in the Mekong Delta: Linking water quality, shrimp and their natural food sources. Science Of The Total Environment, 739, 139931. Read online
  77. Leuchtenberger, A. F., Crotty, S. M., Drucks, T., Schmidt, H. A., Burgstaller-Muehlbacher, S., & von Haeseler, A. (2020). Distinguishing Felsenstein Zone from Farris Zone Using Neural Networks. Molecular Biology And Evolution, 37(12), 3632-3641. Read online
  78. Li, C., Xie, H. - B., Mengersen, K. L., Fan, X., Da Xu, R. Yi, Sisson, S., & Van Huffel, S. (2020). Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures. IEEE Transactions On Signal Processing, 68, 3860 - 3870. Read online
  79. Li, L., Liu, F., Feng, L., & Turner, I. (2020). A Galerkin finite element method for the modified distributed-order anomalous sub-diffusion equation. Journal Of Computational And Applied Mathematics, 368, 112589. Read online
  80. Lin, Y. -F., Duan, Q., Zhou, Y., Yuan, T., Li, P., Fitzpatrick, T., Fu, L., Feng, A., Luo, G., Zhan, Y., Liang, B., Fan, S., Lu, Y., Wang, B., Wang, Z., Zhao, H., Gao, Y., Li, M., Chen, D., Chen, X., Ao, Y., Li, L., Cai, W., Du, X., Shu, Y., & Zou, H. (2020). Spread and Impact of COVID-19 in China: A Systematic Review and Synthesis of Predictions From Transmission-Dynamic Models. Frontiers In Medicine, 7, 321. Read online
  81. Liu, C., Zhou, S., Wang, Y. - G., & Hu, Z. (2020). Natural mortality estimation using tree-based ensemble learning models. ICES Journal Of Marine Science, 77(4), 1414-1426. Read online
  82. Liu, D., Mitchell, L., Cope, R. C., Carlson, S. J., & Ross, J. V. (2020). Elucidating user behaviours in a digital health surveillance system to correct prevalence estimates. Epidemics, 33, 100404. Read online
  83. McVinish, R., & Lester, R. J. G. (2020). Measuring aggregation in parasite populations. Journal Of The Royal Society Interface, 17(165), 20190886. Read online
  84. Meehan, M. T., Cope, R. C., & McBryde, E. S. (2020). On the probability of strain invasion in endemic settings: accounting for individual heterogeneity and control in multi-strain dynamics. Journal Of Theoretical Biology, 487, 110109. Read online
  85. Mehra, S., McCaw, J. M., Flegg, M. B., Taylor, P. G., & Flegg, J. A. (2020). An Activation-Clearance Model for Plasmodium vivax Malaria. Bulletin Of Mathematical Biology, 82(2), 32. Read online
  86. Mendes, E. F., Carter, C. K., Gunawan, D., & Kohn, R. (2020). A Flexible particle Markov chain Monte Carlo Method. Statistics And Computing, 30, 783-798. Read online
  87. Mohajerpoor, R., Saberi, M., Vu, H. L., Garoni, T. M., & Ramezani, M. (2020). H∞ robust perimeter flow control in urban networks with partial information feedback. Transportation Research Part B: Methodological, 137, 47-73. Read online
  88. Moka, S. Babu, & Kroese, D. (2020). Perfect Sampling for Gibbs Point Processes using Partial Rejection Sampling. Bernoulli, 26(3), 2082-2104. Read online
  89. Moores, M., Nicholls, G., Pettitt, A., & Mengersen, K. L. (2020). Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model. Bayesian Analysis, 15(1), 1-27. Read online
  90. Nguyen, G. T., & Peralta, O. (2020). An explicit solution to the Skorokhod embedding problem for double exponential increments. Statistics & Probability Letters, 165, 108867. Read online
  91. Parker, C., Rohrlach, A. B., Friederich, S., Nagel, S., Meyer, M., Krause, J., Bos, K. I., & Haak, W. (2020). A systematic investigation of human DNA preservation in medieval skeletons. Scientific Reports, 10(1), 18225. Read online
  92. Pearse, A. R., McGree, J. M., Som, N. A., Leigh, C., Maxwell, P., Ver Hoef, J. M., & Peterson, E. E. (2020). SSNdesign—An R package for pseudo-Bayesian optimal and adaptive sampling designs on stream networks. PLOS One, 15(9), e0238422. Read online
  93. Perez, J. Rodriguez, Leigh, C., Liquet, B., Kermorvant, C., Peterson, E., Sous, D., & Mengersen, K. L. (2020). Detecting technical anomalies in high-frequency water-quality data using Artificial Neural Networks. Environmental Science & Technology, 54(21), 13719-13730. Read online
  94. Peterson, E. E., Santos-Fernández, E., Chen, C., Clifford, S., Vercelloni, J., Pearse, A., Brown, R., Christensen, B., James, A., Anthony, K., Loder, J., González-Rivero, M., Roelfsema, C., Caley, M. J., Mellin, C., Bednarz, T., & Mengersen, K. (2020). Monitoring through many eyes: Integrating disparate datasets to improve monitoring of the Great Barrier Reef. Environmental Modelling & Software, 124, 104557. Read online
  95. Quella, T. (2020). On conformal field theories based on Takiff superalgebras. Journal Of Physics Communications, 4(7), 075013. Read online
  96. Quella, T. (2020). Symmetry-protected topological phases beyond groups: The q-deformed Affleck-Kennedy-Lieb-Tasaki model. Physical Review B, 102(8), 081120. Read online
  97. Quella, T., & Roy, A. (2020). Conformal field theory and the non-abelian SU(2)kchiral spin liquid. Journal Of Statistical Mechanics: Theory And Experiment, 2020(5), 053107. Read online
  98. Quill, R., Sharples, J. J., & Sidhu, L. A. (2020). A Statistical Approach to Understanding Canopy Winds over Complex Terrain. Environmental Modeling & Assessment, 25, 231-250. Read online
  99. Rivollat, M., Jeong, C., Schiffels, S., Küçükkalıpçı, İ., Pemonge, M. - H., Rohrlach, A. B., Alt, K. W., Binder, D., Friederich, S., Ghesquière, E., Gronenborn, D., Laporte, L., Lefranc, P., Meller, H., Réveillas, H., Rosenstock, E., Rottier, S., Scarre, C., Soler, L., Wahl, J., Krause, J., Deguillox, M. -F., & Haak, W. (2020). Ancient genome-wide DNA from France highlights the complexity of interactions between Mesolithic hunter-gatherers and Neolithic farmers. Science Advances, 6(22), eaaz5344. Read online
  100. Rodrigues, G. S., Nott, D. J., & Sisson, S. A. (2020). Likelihood-free approximate Gibbs sampling. Statistics And Computing, 30(4), 1057 - 1073. Read online
  101. Rodriguez-Ramirez, A., González-Rivero, M., Beijbom, O., Bailhache, C., Bongaerts, P., Brown, K. T., Bryant, D. E. P., Dalton, P., Dove, S., Ganase, A., Kennedy, E. V., Kim, C. J. S., Lopez-Marcano, S., Neal, B. P., Radice, V. Z., Vercelloni, J., Beyer, H. L., & Hoegh-Guldberg, O. (2020). A contemporary baseline record of the world’s coral reefs. Scientific Data, 7(1), 355. Read online
  102. Roughan, M., Mitchell, L., & South, T. (2020). How the Avengers assemble: Ecological modelling of effective cast sizes for movies. PLOS One, 15(2), e0223833. Read online
  103. Samuelson, A., O’Reilly, M. M., & Bean, N. G. (2020). Construction of algorithms for discrete-time quasi-birth-and-death processes through physical interpretation. Stochastic Models, 36(2), 193 - 222. Read online
  104. Sharp, J. A., Browning, A. P., Mapder, T., Baker, C. M., Burrage, K., & Simpson, M. J. (2020). Designing combination therapies using multiple optimal controls. Journal Of Theoretical Biology, 497, 110277. Read online
  105. Shukla, A., Nguyen, T. H. M., Moka, S. Babu, Ellis, J. J., Grady, J. P., Oey, H., Cristino, A. S., Khanna, K. K., Kroese, D. P., Krause, L., Dray, E., Fink, J. L., & Duijf, P. H. G.(2020). Chromosome Arm Aneuploidies Shape Tumour Evolution, Cancer Prognosis and Drug Response. Nature Communications, 11(1), 449. Read online
  106. Simon, M. (2020). SIR epidemics with stochastic infectious periods. Stochastic Processes And Their Applications, 130(7), 4252-4274. Read online
  107. Skourtanioti, E., Erdal, Y. S., Frangipane, M., Restelli, F. Balossi, K. Yener, A., Pinnock, F., Matthiae, P., Özbal, R., Schoop, U. -D., Guliyev, F., Akhundov, T., Lyonnet, B., Hammer, E. L., Nugent, S. E., Burri, M., Neumann, G. U., Penske, S., Ingman, T., Akar, M., Shafiq, R., Palumbi, G., Eisenmann, S., D’Andrea, M., Rohrlach, A. B., Warinner, C., Jeong, C., Stockhammer, P. W., Haak, W., & Krause, J. (2020). Genomic History of Neolithic to Bronze Age Anatolia, Northern Levant, and Southern Caucasus. Cell, 181(5), 1158 - 1175.e28. Read online
  108. Talagala, P. Dilini, Hyndman, R. J., Smith-Miles, K., Kandanaarachchi, S., & Muñoz, M. A. (2020). Anomaly Detection in Streaming Nonstationary Temporal Data. Journal Of Computational And Graphical Statistics, 29(1), 13-27. Read online
  109. Tran, M. - N., Nguyen, N., Nott, D., & Kohn, R. (2020). Bayesian Deep Net GLM and GLMM. Journal Of Computational And Graphical Statistics, 29, 97-113. Read online
  110. Tuke, J., Nguyen, A., Nasim, M., Mellor, D., Wickramasinghe, A., Bean, N. G., & Mitchell, L. (2020). Pachinko Prediction: A Bayesian method for event prediction from social media data. Information Processing & Management, 57(2), 102147. Read online
  111. Vaisman, R. (2020). Subset selection via continuous optimization with applications to network design. Environmental Monitoring And Assessment, 192(6), 361. Read online
  112. Varghese, A., Drovandi, C., Mira, A., & Mengersen, K. (2020). Estimating a novel stochastic model for within-field disease dynamics of banana bunchy top virus via approximate Bayesian computation. PLOS Computational Biology, 16(5), e1007878. Read online
  113. Vercelloni, J., Liquet, B., Kennedy, E. V., González‐Rivero, M., M. Caley, J., Peterson, E. E., Puotinen, M., Hoegh‐Guldberg, O., & Mengersen, K. (2020). Forecasting intensifying disturbance effects on coral reefs. Global Change Biology, 26(5), 2785 - 2797. Read online
  114. Warne, D. J., Ebert, A., Drovandi, C., Hu, W., Mira, A., & Mengersen, K. L. (2020). Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic. BMC Public Health, 20, 1868. Read online
  115. Wei, C., Hu, Z. - H., & Wang, Y. - G. (2020). Exact algorithms for energy-efficient virtual machine placement in data centers. Future Generation Computer Systems, 106, 77 - 91. Read online
  116. Whitaker, T., Béranger, B., & Sisson, S. A. (2020). Composite likelihood methods for histogram-valued random variables. Statistics And Computing, 30(5), 1459 - 1477. Read online
  117. Wilson-Stewart, K. S., Fontanarosa, D., Li, D., Drovandi, C. C., Anderson, R. K., & Trapp, J. V. (2020). Taller staff occupationally exposed to less radiation to the temple in cardiac procedures, but risk higher doses during vascular cases. Scientific Reports, 10, 16103. Read online
  118. Wu, J., Wang, Y. - G., Burrage, K., Tian, Y. - C., Lawson, B., & Ding, Z. (2020). An improved firefly algorithm for global continuous optimization problems. Expert Systems With Applications, 149, 113340. Read online
  119. Xu, P., Roosta, F., & Mahoney, M. W. (2020). Newton-type methods for non-convex optimization under inexact Hessian information. Mathematical Programming, 184, 35-70. Read online
  120. Yang, S., Liu, F., Feng, L., & Turner, I. (2020). Efficient numerical methods for the nonlinear two-sided space-fractional diffusion equation with variable coefficients. Applied Numerical Mathematics, 157, 55 - 68. Read online
  121. Yang, Y., Ge, J., Yue, D., Meng, Q., & Wu, J. (2020). Adaptive Resilient Control of a Class of Nonlinear Systems Based on Event-Triggered Mechanism. Neurocomputing, 403, 304-313. Read online
  122. Yang, Z., Liu, F., Nie, Y., & Turner, I. (2020). An unstructured mesh finite difference/finite element method for the three-dimensional time-space fractional Bloch-Torrey equations on irregular domains. Journal Of Computational Physics, 408, 109284. Read online
  123. Zhang, X., Béranger, B., & Sisson, S. (2020). Constructing likelihood functions for interval‐valued random variables. Scandinavian Journal Of Statistics, 47(1), 1-35. Read online
  124. Zhang, Y., Bambrick, H., Mengersen, K., Tong, S., Feng, L., Liu, G., Xu, A., Zhang, L., & Hu, W. (2020). Association of weather variability with resurging pertussis infections among different age groups: A non-linear approach. Science Of The Total Environment, 719, 137510. Read online
  125. Zhang, Y., Bambrick, H., Mengersen, K., Tong, S., Feng, L., Zhang, L., Liu, G., Xu, A., Hu, W. (2020). Using big data to predict pertussis infections in Jinan city, China: a time series analysis. International Journal Of Biometeorology, 64(1), 95 - 104. Read online
  126. Zheng, R., Liu, F., Jiang, X., & Turner, I. (2020). Finite difference/spectral methods for the two-dimensional distributed-order time-fractional cable equation. Computers & Mathematics With Applications, 80(6), 1523 - 1537. Read online
Non-refereed article
  1. Balnozan, I., Fiebig, D. G., Asher, A., Kohn, R., & Sisson, S. (2020). Hidden Group Time Profiles: Heterogeneous Drawdown Behaviours in Retirement. Arxiv, arXiv:2009.01505v1. Read online
  2. Bardsley, J., & Cui, T. (2020). Optimization-Based MCMC Methods for Nonlinear Hierarchical Statistical Inverse Problems. Arxiv, arXiv:2002.06358v1. Retrieved fromRead online
  3. Borg, D. N., Nguyen, R., & Tierney, N. (2020). Missing Data: Current Practice in Football Research and Recommendations for Improvement. Sportrxiv, Nov 2020. Read online
  4. Burrage, K., Burrage, P., & MacNamara, S. (2020). The reflectionless properties of Toeplitz waves and Hankel waves: an analysis via Bessel functions. Arxiv, arXiv:2005.04561. Read online
  5. Cui, T., & Dolgov, S. (2020). Deep Composition of Tensor Trains using Squared Inverse Rosenblatt Transports. Arxiv, arXiv:2007.06968v1. Read online
  6. Dandekar, R., Henderson, S. G., Jansen, H. M., McDonald, J., Moka, S. Babu, Nazarathy, Y., Rackauckas, C., Taylor, P. G., & Vourinen, A. (2020). Safe Blues: A Method for Estimation and Control in the Fight Against COVID-19. Medrxiv. Read online
  7. Dang, K. - D., Ryan, L. M., Akkaya-Hocagil, T., Cook, R. J., Richardson, G. A., Day, N. L., Coles, C. D., Olson, H. C., Jacobson, S. W., & Jacobson, J. L. (2020). Bayesian Structural Equation Modeling for data from multiple cohorts. Arxiv, arXiv:2012.12085v1. Read online
  8. Fang, S., Zhou, Z., & Deng, Y. (2020). Percolation effects in the Fortuin-Kasteleyn Ising model on the complete graph. Arxiv, arXiv:2008.07256v1. Read online
  9. Frazier, D. T., Drovandi, C. C., & Loaiza-Maya, R. (2020). Robust Approximate Bayesian Computation: An Adjustment Approach. Arxiv, arXiv:2008.04099v1. Read online
  10. Gupta, S., Hyndman, R. J., Cook, D., & Unwin, A. (2020). Visualizing probability distributions across bivariate cyclic temporal granularities. Read online
  11. Herath, S., Roughan, M., & Glonek, G. (2020). Simulating Name-like Vectors for Testing Large-scale Entity Resolution. Arxiv, arXiv:2009.03014v1. Read online
  12. Hirsch, C., Moka, S. Babu, Taimre, T., & Kroese, D. P. (2020). Rare Events in Random Geometric Graphs. Arxiv, arXiv:2007.05965v1. Read online
  13. Hodgkinson, L., Salomone, R., & Roosta, F. (2020). The reproducing Stein kernel approach for post-hoc corrected sampling. Arxiv, arXiv:2001:09266v1. Read online
  14. Jaeger, B. C., Tierney, N. J., & Simon, N. R. (2020). When to Impute? Imputation before and during cross-validation. Arxiv, arXiv:2010.00718v1. Read online
  15. Loaiza-Maya, R., Martin, G. M., & Frazier, D. T. (2020). Focused Bayesian Prediction. Arxiv, arXiv:1912.12571. Read online
  16. Martin, G. M., Frazier, D. T., & Robert, C. P. (2020). Computing Bayes: Bayesian Computation from 1763 to the 21st Century. Arxiv, arXiv:2004.06425v2. Read online
  17. Martin, G. M., Loaiza-Maya, R., Frazier, D. T., Maneesoonthorn, W., & Hassan, A. Ramirez. (2020). Optimal probabilistic forecasts: When do they work? Arxiv, arXiv:2009.09592v1. Read online
  18. Moka, S. Babu, Nazarathy, Y., & Scheinhardt, W. (2020). Diffusion Parameters of Flows in Stable Multi-class Queueing Networks. Arxiv, arXiv:1311.5610v2. Read online
  19. Priddle, J. W., Sisson, S. A., Frazier, D. T., & Drovandi, C. (2020). Efficient Bayesian synthetic likelihood with whitening transformations. Arxiv, arXiv:1909.04857v2. Read online
  20. Tierney, N. J., & Ram, K. (2020). A Realistic Guide to Making Data Available Alongside Code to Improve Reproducibility. Arxiv, arXiv:2002.11626v1. Read online
  21. Wang, X., Kang, Y., Hyndman, R. J., & Li, F. (2020). Distributed ARIMA Models for Ultra-long Time Series. Arxiv, arXiv:2007.09577v1. Read online
  22. Warne, D., Ebert, A., Drovandi, C., Hu, W., Mira, A., & Mengersen, K. L. (2020). Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic. Medrxiv. Read online
  23. Warne, D. J., Sisson, S. A., & Drovandi, C. (2020). Vector operations for accelerating expensive Bayesian computations -- a tutorial guide. Arxiv, arXiv:1902.09046v3. Read online
  24. Zhou, Z., Grimm, J., Deng, Y., & Garoni, T. (2020). Random-length Random Walks and Finite-size Scaling on high-dimensional hypercubic lattices I: Periodic Boundary Conditions. Arxiv, arXiv:2008.00913v1. Read online
Letter or note
  1. Borg, D. N., Bon, J. J., Sainani, K. L., Baguley, B. J., Tierney, N. J., & Drovandi, C. (2020). Comment on: ‘Moving Sport and Exercise Science Forward: A Call for the Adoption of More Transparent Research Practices’. Sports Medicine, 50(8), 1551 - 1553. Read online
  2. Jiang, Y., Yuan, Z., Hu, H., Ye, X., Zheng, Z., Wei, Y., Zheng, Y. -L., Wang, Y. -G., & Liu, C. (2020). Differentiating homoploid hybridization from ancestral subdivision in evaluating the origin of the D lineage in wheat. New Phytologist, 228(2), 409 - 414. Read online

Invited talks, refereed proceedings and other conference outputs

Full written conference paper (refereed - must be peer reviewed and presented)
  1. Ali, T. F., & Woodley, A. (2020). Using Environmental Context to Synthesis Missing Pixels. 2020 Digital Image Computing: Techniques and Applications (DICTA). Virtual. Read online
  2. Crane, R., & Roosta, F. (2020). DINO: Distributed Newton-Type Optimization Method. Proceedings of the 37th International Conference on Machine Learning (Vol. 119, pp. 2174–2184). Virtual: PMLR. Read online
  3. Cui, Z., Hou, X., Zhou, H., Lian, W., & Wu, J. (2020). Modified Slime Mould Algorithm via Levy Flight. 2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) (pp. 1109 - 1113). Chengdu, China: IEEE. Read online
  4. Dennis-Henderson, A., Roughan, M., Mitchell, L., & Tuke, J. (2020). Life still goes on: Analysing Australian WW1 Diaries through Distant Reading. Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (pp. 90-104). Virtual. Read online
  5. Edwards, M., Tuke, J., Roughan, M., & Mitchell, L. (2020). The one comparing narrative social network extraction techniques. 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Virtual: IEEE. Read online
  6. Jony, R. Islam, Woodley, A., & Perrin, D. (2020). Fusing Visual Features and Metadata to Detect Flooding in Flickr Images. 2020 Digital Image Computing: Techniques and Applications (DICTA). Virtual: IEEE. Read online
  7. MacNamara, S., Blanes, S., & Iserles, A. (2020). Simulation of bimolecular reactions: Numerical challenges with the graph Laplacian. 14th Engineering Mathematics and Applications Conference (Vol. 61, pp. C59 - C74). Canberra, Australia. Read online
  8. McLaughlin, C., Woodley, A., Geva, S., Chappell, T., Kelly, W., Boles, W., De Vine, L., & Hutson, H. (2020). Object Based Remote Sensing Using Sentinel Data. 2020 Digital Image Computing: Techniques and Applications (DICTA). Virtual. Read online
  9. Salomone, R., Quiroz, M., Kohn, R., Villani, M., & Tran, M. - N. (2020). Spectral Subsampling MCMC for Stationary Time Series. Proceedings of the 37th International Conference on Machine Learning (Vol. 119, pp. 8449-8458). Wien: PMLR. Read online
  10. Weber, D., Nasim, M., Mitchell, L., & Falzon, L. (2020). A method to evaluate the reliability of social media data for social network analysis. 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Netherlands: 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). Read online
  11. Xu, P., Roosta, F., & Mahoney, M. W. (2020). Second-order Optimization for Non-convex Machine Learning: an Empirical Study. 2020 SIAM International Conference on Data Mining (pp. 199 - 207). Philadelphia, PA: Society for Industrial and Applied Mathematics. Read online
  12. Zhang, B., Yang, Y., Zhao, D., & Wu, J. (2020). A robust decomposition-ensemble framework for wind speed forecasting. 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV) (p. 9305351). Shenzhen, China: IEEE. Read online
Full written paper (non refereed - not subject to peer review but were formally assessed by an editorial board)
  1. Roughan, M. (2020). Video Assessment Tasks in Tertiary Education: Practice and Experience in STEM. Teaching and Learning Computer Networking During the Pandemic and Beyond. Virtual. Read online
  2. Whyte, J. M. (2020). On Using ‘Emerging Interest’ in Scientific Literature to Inform Chemical Risk Prioritisation. Proceedings of the 10th International Environmental Modelling and Software Society Conference. Brussels, Belgium: Brigham Young University. Read online
Extract of paper (abstracts, extracts and synopses of conference papers that are subsequently published)
  1. Herath, S., Roughan, M., & Glonek, G. (2020). Landmarks-based Blocking Method For Large-scale Entity Resolution. 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA). Sydney, Australia, Australia: IEEE. Read online
  2. Hu, S. (2020). Inclusion of features derived from a mixture of time window sizes improved classification accuracy of machine learning algorithms for sheep grazing behaviours. Data Science Workshop. QUT, Brisbane.
Unpublished presentation or other conference paper (where none of the above categories are met. For example, published on conference website or program.)
  1. Adams, M. P., Sisson, S., O'Brien, K. R., Helmstedt, K. J., Baker, C. M., Koh, E. J. Y., Vilas, M. P., Collier, C. J., Holden, M. H., Lambert, V. M., Quiroz, M., Plein, M., Holloway, J., Mengersen, K. L., McKenzie, L., & McDonald-Madden, E. (2020). Propagating uncertainty through to model forecasts: deterministic Lotka-Volterra systems as a case study. Quantitative Ecology Virtual Meeting 2020. Virtual.
  2. Bon, J. J., Lee, A., & Drovandi, C. (2020). Delayed-acceptance Sequential Monte Carlo. Virtual invited seminar at MRC Biostatistics Unit, Cambridge University. Virtual. Read online
  3. Botha, I., Drovandi, C., South, L., & Kohn, R. (2020). Tuning the number of state particles in exact-approximate SMC. Bayesian Young Statisticians Meeting: Online (BAYSM:O). Virtual.
  4. Browning, A. P., Haridas, P., & Simpson, M. J. (2020). Parameterising mathematical models of melanoma invasion through a sequence of experiments. Brisbane Cancer Conference. Brisbane, Australia.
  5. Browning, A. P., Warne, D., Burrage, K., Baker, R. E., & Simpson, M. J. (2020). Parameter identifiability for mechanistic models in biology. ACEMS 2020 Virtual Retreat. Virtual.
  6. Cramb, S., & Mengersen, K. (2020). Bayesian multivariate analysis of disease, with application to the Australian Cancer Atlas. 2020 Joint Statistical Meetings. Virtual.
  7. Crotty, S. M. (2020). Maximum Likelihood by Proxy. New Zealand Phylogenomics Meeting. Waiheke Island, New Zealand.
  8. Crotty, S. M. (2020). Phylogenomic signal mapping. Phylomania 2020. Virtual.
  9. Dang, K. - D., Ryan, L. M., Akkaya-Hocagil, T., Cook, R. J., Richardson, G. A., Day, N. L., Coles, C. D., Olson, H. C., Jacobson, S. W., & Jacobson, J. L. (2020). A Bayesian Structural Equation Model for data from multiple studies. The 30th International Biometric Conference. Virtual.
  10. Drovandi, C. (2020). ACEMS RSS Funding Outcomes. ACEMS 2020 Virtual Retreat. Virtual.
  11. Drovandi, C. (2020). Accelerating sequential Monte Carlo with surrogate likelihoods. Research seminar for Chalmers University of Technology, Sweden (Webinar). Virtual.
  12. Drovandi, C. (2020). Improving Bayesian Synthetic Likelihood via Transformations. One World Approximate Bayesian Computation. One World Approximate Bayesian Computation (Webinar). Virtual.
  13. Farquhar, M., Lawson, B., & Burrage, K. (2020). Graph-based Homogenization techniques for modelling cardiac fibrosis. ANZIAM 2020. Hunter Valley, NSW.
  14. Holloway-Brown, J. (2020). Earth Observation for agriculture, environment and oceans: Developing data science methods and capability. United Nations 6th International Conference on Big Data for Official Statistics. Virtual.
  15. Humphries, M. (2020). Counting Our Virus In Dung - An introduction to wastewater based epidemiology. ACEMS 2020 Virtual Retreat. Virtual.
  16. Maestrini, L., Aykroyd, R., & Wand, M. (2020). Variational Approximate Inference for Inverse Problems Motivated by Medical Tomography. International Biometric Conference 2020. Virtual.
  17. Mengersen, K. (2020). Back to the Future: ranking and selection. 64th Annual Meeting of the Australian Mathematical Society AustMS. Virtual.
  18. Mengersen, K. (2020). Campion (President's Invited) Lecturer, Royal Statistical Society Conference, September Online Conference. Royal Statistical Society Conference - September. Virtual.
  19. Mengersen, K. (2020). Inaugural Online Speaker: Pearcey Foundation Celebration of Ada Lovelace Day Tuesday 13 October 2020 - Women's Contributions to the Digital Age. Pearcey Foundation Celebration of Ada Lovelace Day. Virtual.
  20. Mengersen, K. (2020). Invited Plenary Speaker, Bernoulli-IMS One World Virtual Symposium. Bernoulli-IMS One World Symposium 2020. Virtual.
  21. Mengersen, K. (2020). Invited Seminar, Department of Statistical Sciences, University of Padova, Italy - February. Seminar, Department of Statistical Sciences, University of Padova, Italy. Padova, Italy.
  22. Mengersen, K. (2020). Invited Seminar, Swiss University for Applied Sciences ZHAW Datahub, Zurich – January. Swiss University for Applied Sciences ZHAW Datahub Seminar, Zurich. Zurich, Switzerland.
  23. Mengersen, K. (2020). Invited Seminar, University of Pavia, Italy - February. University of Pavia Seminar, Italy. Pavia, Italy.
  24. Mengersen, K. (2020). Invited Speaker, 6th International Conference on Big Data for Official Statistics, United Nations Statistics Division - September. 6th International Conference on Big Data for Official Statistics, United Nations Statistics Division. Virtual.
  25. Mengersen, K. (2020). Online Keynote Speaker, United Nations Inauguration Ceremony of the Regional Hub for Big Data in China. United Nations Inauguration Ceremony of the Regional Hub for Big Data in China. Virtual.
  26. Mengersen, K. (2020). Online Panellist, Women in Mathematics Special Interest Group. Women in Mathematics Special Interest Group AustMS. Virtual.
  27. Mengersen, K. (2020). Online Presenter, AustMS Early-Career Workshop. Aust MS Early-Career Workshop. Virtual.
  28. Mengersen, K. (2020). Online Seminar, ARC Centre for Data Analytics for Resources and Environments (DARE) Sydney - June. ARC Centre for Data Analytics for Resources and Environments Seminar, Sydney. Virtual.
  29. Mengersen, K. (2020). Online Seminar, Statistics across Campus, Sydney University - June. Statistics Across Campus Seminar, Sydney University. Virtual.
  30. Mengersen, K. (2020). Online Statistics Seminar, University of Melbourne - July. Statistics Seminar, University of Melbourne. Virtual.
  31. Mengersen, K. (2020). Presenter, AMSI BioInfoSummer Online Conference 2020. AMSI BioInfoSummer Online Conference 2020. Virtual.
  32. Mengersen, K. (2020). Presenter, Indian Institute of Technology Madras, QUT/IIT-M Virtual Workshop. Indian Institute of Technology Madras, QUT/IIT-M Virtual Workshop. Virtual.
  33. Mengersen, K. (2020). Writing Successful Fellowships - Statistical Society of Australia Webinar - July. Statistical Society of Australia Webinar. Virtual.
  34. Moka, S. B., Hirsch, C., Kroese, D. P., Taimre, T., & Schmidt, V. (2020). Rare-Event Simulation for Random Geometric Graphs. 64th Annual Meeting of the Australian Mathematical Society. Virtual.
  35. Moka, S. B., Kroese, D. P., Hirsch, C., Schmidt, V., & Taimre, T. (2020). Rare-Event Simulation for Random Geometric Graphs. ACEMS 2020 Virtual Retreat. Virtual.
  36. Niknami, B., & Taylor, P. (2020). Double Auctions with Dynamic Utility. ANZIAM 2020. Hunter Valley, NSW.
  37. Pollett, P. (2020). Health system demand and the spread of COVID-19. ACEMS COVID-19 Research Workshop. Virtual.
  38. Pollett, P., & Hodgkinson, L. (2020). High-density limits for infinite occupancy processes. 64th Annual Meeting of the Australian Mathematical Society. Virtual.
  39. Psaltis, S., Timms, R., Please, C., & S. Chapman, J. (2020). Homogenisation of connected, layered materials with large rapid spatial variations in conductivity - simplified models of cylindrical batteries. ANZIAM 2020. Hunter Valley, NSW.
  40. Psaltis, S., Turner, I., Farrell, T., Carr, E. J., Bailleres, H., Kumar, C., Brancheriau, L., & Lee, D. (2020). Prediction of sawn timber MOE from increment cores. The 20th Biennial Computational Techniques and Applications Conference (CTAC2020). Virtual.
  41. Roughan, M. (2020). The Colour of Magic by Numbers. The Pratchett Project Conference. Virtual.
  42. Sulem, D., Mengersen, K. L., Rivoirard, V., & Rousseau, J. (2020). Modelling the spread of COVID-19 with Hawkes processes. ACEMS COVID-19 Research Workshop. Virtual.
  43. Sulem, D., Mengersen, K. L., Rivoirard, V., & Rousseau, J. (2020). Simple discrete-time self-exciting models can describe complex dynamic processes: a case study of COVID-19. ACEMS 2020 Virtual Retreat. Virtual.
  44. Tierney, N. J. (2020). Making better spaghetti (plots): Exploring the individuals in longitudinal data with the brolgar package. RStudio Conference 2020. San Francisco: RStudio Conference 2020. Read online
  45. Tierney, N. J., & Ram, K. (2020). Data Data Data. Invited Seminar, University of Washington. Seattle, USA: University of Washington. Read online
  46. Tierney, N. J., & Ram, K. (2020). Data Data Data. Invited talk, Sage Bionetworks. Seattle, USA: Sage Bionetworks. Read online
  47. Tierney, N. J., & Ram, K. (2020). Data Data Data. NUMBAT seminar, Monash University. Melbourne: NUMBAT seminar, Monash. Read online
  48. Tuke, J., & Humphries, M. A. (2020). Teaching through community. Festival of Learning and Teaching 2020. Adelaide.
  49. Vercelloni, J. (2020). Global patterns of community assembly on coral reefs. International Statistical Ecological Conference. Virtual.
  50. Vercelloni, J. (2020). Going for gold – data, data science and elite sports. In Data Science In The News Webinar. Virtual.
  51. Warne, D., Ebert, A., Drovandi, C., Mira, A., & Mengersen, K. L. (2020). Characterisation of the global response to the COVID-19 pandemic. ACEMS COVID‐19 Research Workshop. Virtual. Read online
  52. Warne, D. J., Crossman, K. A., Jin, W., Mengersen, K. L., Osborne, K., Simpson, M. J., Thompson, A. A., Wu, P., & Ortiz, J. (2020). Identification of two-phase recovery in hard corals across the Great Barrier Reef. ACEMS 2020 Virtual Retreat. Virtual. Read online
  53. Whyte, J. M. (2020). Branching out into structural identifiability analysis with Maple. In J. M. Whyte (Ed.), J. M. Whyte (Tran.), Maple Conference 2020. Virtual.
  54. Whyte, J. M. (2020). Frustrated mathematical modelling and changeable destinies: Structural identifiability analysis of models to support useful results. Seminario de Investigación Interdisciplinar para la Innovación en Ciencia y Tecnología (SICTE). Universidad Católica del Norte, Chile.
  55. Whyte, J. M. (2020). On Using ‘Emerging Interest’ in Scientific Literature to Inform Chemical Risk Prioritisation (with updates). Emerging Contaminants Workshop 2020. Virtual.
  56. Wu, P. (2020). Practical Data Science – Data, models, and tall tales. Sports Technology and Applied Research Symposium. Virtual.
  57. Wu, P. Pao- Yen, M Claey, J., Kendrick, G. A., McMahon, K., & Mengersen, K. (2020). Dynamic Bayesian network inferencing for non-homogeneous complex systems. Twelfth Annual Conference of the Australasian Bayesian Network Modelling Society (ABNMS2020). Virtual.

Publicly available software

Software and computing packages
  1. Adams, M. P., Koh, E. J. Y., Vilas, M. P., Collier, C. J., Lambert, V. M., Sisson, S. A., Quiroz, M., McDonald-Madden, E., McKenzie, L. J., & O'Brien, K. R. (2020). Seagrass Cumulative Stress Index (CSI) Program: Software for "Predicting seagrass decline due to cumulative stressors". Read online
  2. Adams, M. P., Sisson, S., Helmstedt, K. J., Baker, C. M., Holden, M. H., Plein, M., Holloway, J., Mengersen, K. L., & McDonald-Madden, E. (2020). Code and selected model outputs for "Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data". Read online
  3. Browning, A. P., Jin, W., Plank, M. J., & Simpson, M. J. (2020). scratchIBM. Read online
  4. Browning, A. P., Warne, D. J., Burrage, K., Baker, R. E., & Simpson, M. J. (2020). SDE-Identifiability. Read online
  5. Drovandi, C., & Warne, D. J. (2020). Bayesian analysis of the COVID-19 pandemic.
  6. Kandanaarachchi, S. (2020). airt. Read online
  7. Kandanaarachchi, S., Menendez, P., Laa, U., & Loaiza-Maya, R. (2020). composits. Read online
  8. Kang, Y., Li, F., Hyndman, R., O'Hara-Wild, M., & Zhao, B. (2020). gratis. Read online
  9. Matamoros, A. Alonzo, Nieto-Reyes, A., Hyndman, R., O'Hara-Wild, M., & Trapletti, A. (2020). nortsTest. Read online
  10. Moores, M., Nicholls, G., Pettitt, A., & Mengersen, K. (2020). Supplemental Content: March 2020 Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model. Read online
  11. O'Hara-Wild, M., Taylor, S., & Letham, B. (2020). fable.prophet. Read online
  12. O'Hara-Wild, M., Wang, E., Kay, M., & Hayes, A. (2020). distributional. Read online
  13. Talagala, T., Hyndman, R. J., & Athanasopoulos, G. (2020). seer. Read online
  14. Tierney, N. J., Cook, D., & Prvan, T. (2020). brolgar. Read online
  15. Varghese, A., Drovandi, C., Mira, A., & Mengersen, K. (2020). Source code: Estimating a novel stochastic model for within-field disease dynamics of banana bunchy top virus via approximate Bayesian computation. Read online
  16. Wang, E., & Cook, D. (2020). tsibbletalk. Read online
  17. Warne, D., Sisson, S., & Drovandi, C. (2020). Bayesian computations using SIMD operations. Read online
Data Sets
  1. Alahmadi, A. A., Flegg, J. A., Cochrane, D. G., Drovandi, C. C., & Keith, J. M. (2020). Run_file_Malariah from A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models. Read online
  2. Talagala, T. S., Wanniarachchi, J. C., De Mel, C. R., Lakshika, J., De Silva, S., Dananjana, T., Piyumika, H., Wijesuriya, R., Fernando, M., Madushani, N. N., Madushani, S. N., De Mel, V. P. C., & Ranathunga, O. (2020). Read online

Technical reports and unrefereed outputs

Unpublished Reports
  1. Ryan, L. M. (2020). Namoi Valley groundwater level modelling report.
  2. Warne, D., & Ortiz, J. - C. (2020). Power analysis for recovery delay detection.
  3. Warne, D. J., & Ortiz, J. - C. (2020). Charaterisation of Early Recovery Periods within the Great Barrier Reef: Progress Report.