Select Publications
Journal articles
2008, 'Evaluating extreme risks in invasion ecology: learning from banking compliance', Diversity and Distributions, 14, pp. 581 - 591
,2007, 'A distance-based diagnostic for trans-dimensional Markov chains', Statistics and Computing, 17, pp. 357 - 367
,2007, 'Genetics and stochastic simulation do mix!', American Statistician, 61, pp. 112 - 119
,2007, 'Inference for stereological extremes', Journal of the American Statistical Association, 102, pp. 84 - 92
,2007, 'Sequential Monte Carlo without likelihoods', Proceedings of the National Academy of Sciences of the United States of America, 104, pp. 1760 - 1765
,2006, 'Book Reviews', Journal of the Royal Statistical Society Series A: Statistics in Society, 169, pp. 168 - 169, http://dx.doi.org/10.1111/j.1467-985x.2005.00395_2.x
,2006, 'A case for a reassessment of the risks of extreme hydrological hazards in the Caribbean', Stochastic Environmental Research and Risk Assessment, 20, pp. 296 - 306, http://dx.doi.org/10.1007/s00477-005-0246-4
,2006, 'A note on bayesian analyses of capture-recapture data with perfect recaptures', Communications in Statistics - Theory and Methods, 35, pp. 53 - 62, http://dx.doi.org/10.1080/03610920500439612
,2006, 'Bayesian inference, Monte Carlo sampling and operational risk', The Journal of Operational Risk, 1, pp. 27 - 50
,2006, 'Statistics of extremes: Theory and applications', Journal of the Royal Statistical Society Series A - Statistics in Society, 169, pp. 168 - 169
,2006, 'Using approximate Bayesian computation to estimate tuberculosis transmission parameters from genotype data', Genetics, 173, pp. 1511 - 1520, http://dx.doi.org/10.1534/genetics.106.055574
,2005, 'Modelling Dependence Uncertainty in the Extremes of Markov Chains', Extremes, 6, pp. 283 - 300
,2005, 'Statistical inference and simulation for spatial point processes', Journal of the Royal Statistical Society Series A - Statistics in Society, 168, pp. 258 - 259
,2005, 'Trans-dimensional Markov chains: A decade of progress and future perspectives', Journal of the American Statistical Association, 100, pp. 1077 - 1089
,2004, 'Book Reviews', Journal of the Royal Statistical Society Series A: Statistics in Society, 167, pp. 566 - 567, http://dx.doi.org/10.1111/j.1467-985x.2004.02057_3.x
,2004, 'Hidden Markov Models for Bioinformatics', Journal of the Royal Statistical Society Series A: Statistics in Society, 167, pp. 194 - 195, http://dx.doi.org/10.1111/j.1467-985x.2004.298_13.x
,2004, 'Bayesian point estimation of quantitative trait loci', Biometrics, 60, pp. 60 - 68
,2004, 'Bayesian statistics 7', Journal of the Royal Statistical Society Series A - Statistics in Society, 167, pp. 566 - 567
,2003, 'A fully probabilistic approach to extreme rainfall modeling', Journal of Hydrology, 273, pp. 35 - 50, http://dx.doi.org/10.1016/S0022-1694(02)00353-0
,2003, '', Information Retrieval, 6, pp. 275 - 277, http://dx.doi.org/10.1023/a:1023988306026
,2003, 'Book Review: Handbook of statistical genetics', Statistical Methods in Medical Research, 12, pp. 86 - 87, http://dx.doi.org/10.1177/096228020301200109
,2003, 'The Basics of S-PLUS', Journal of the Royal Statistical Society: Series D (The Statistician), 52, pp. 413 - 414, http://dx.doi.org/10.1111/1467-9884.00369_16
,2002, 'Discussion on the meeting on 'statistical modelling and analysis of genetic data'', Journal of the Royal Statistical Society. Series B: Statistical Methodology, 64, pp. 737 - 775, http://dx.doi.org/10.1111/1467-9868.00359
,Conference Papers
2023, 'Free-Form Variational Inference for Gaussian Process State-Space Models', in Proceedings of Machine Learning Research, pp. 9603 - 9622
,2021, 'Bayesian Nonparametric Space Partitions: A Survey', in IJCAI International Joint Conference on Artificial Intelligence, pp. 4408 - 4415
,2021, 'Continuous-time edge modelling using non-parametric point processes', in Advances in Neural Information Processing Systems, pp. 2319 - 2330
,2021, 'Poisson-Randomised DirBN: Large mutation is needed in Dirichlet belief networks', in Proceedings of Machine Learning Research, pp. 3068 - 3077
,2020, 'Online Binary Space Partitioning Forests', in Chiappa S; Calandra R (ed.), INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 108, ADDISON-WESLEY PUBL CO, ELECTR NETWORK, pp. 527 - 536, presented at 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), ELECTR NETWORK, 26 August 2020 - 28 August 2020, http://proceedings.mlr.press/v108/fan20a/fan20a.pdf
,2020, 'Recurrent dirichlet belief networks for interpretable dynamic relational data modelling', in IJCAI International Joint Conference on Artificial Intelligence, pp. 2470 - 2476
,2020, 'Variance reduction properties of the reparameterization trick', in AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics
,2019, 'Scalable deep generative relational model with high-order node dependence', in NeurIPS 2019, 33rd Conference on Neural INformation Processing Systems 2019, Vancouver, Canada, presented at NeurIPS 2019, Vancouver, Canada, 08 December 2019
,2019, 'Binary space partitioning forests', in AISTATS 2019, Proceedings of Machine Learning Research, Naha, Okinawa, Japan, presented at AISTATS 2019, Naha, Okinawa, Japan, 16 April 2019, http://proceedings.mlr.press/v89/fan19b/fan19b.pdf
,2018, 'Rectangular bounding process', in NeurIPS 2018, 32nd Conference on Neural Information Processing Systems, Montreal, presented at NeurIPS 2018, 32nd Conference on Neural Information Processing Systems, Montreal, 03 December 2018 - 08 December 2018
,2018, 'The binary space partitioning tree process', in AISTATS 2018, Proceedings of Machine Learning Research, PMLR, Playa Blanca, Lanzarote, Canary Islands, pp. 1859 - 1867, presented at 21st International Conference on Artificial Intelligence and Statistics : AISTATS 2018, Playa Blanca, Lanzarote, Canary Islands, 09 April 2018 - 11 April 2018, http://proceedings.mlr.press/v84/fan18b/fan18b.pdf
,2014, 'Flood risk estimation in Australia's coastal zone: Modelling the dependence between extreme rainfall and storm surge', in Hydrology and Water Resources Symposium 2014, HWRS 2014 - Conference Proceedings, pp. 390 - 396
,Conference Posters
2020, 'Trends in methamphetamine availability, use, and harms in Australia', presented at The 2020 NDARC Annual Research Symposium, 05 November 2020 - 26 November 2020, https://ndarc.med.unsw.edu.au/resource/trends-methamphetamine-harms-australia
,Reports
2022, Trends in methamphetamine use, markets and harms in Australia, 2003-2019, NDARC, Sydney, http://dx.doi.org/10.26190/ad59-k695
,2021, Submission: Australian Data Strategy Discussion Paper, https://www.allenshub.unsw.edu.au/sites/default/files/inline-files/20210806%20HUB%20AUSCL%20UDASH%20CSI%20DIIU%20CSRI%20submission%20on%20Australian%20Data%20Strategy_0.pdf
,Preprints
2024, Parameter estimation of Gompertz model for tumorgrowth: which likelihood to choose?, , http://dx.doi.org/10.21203/rs.3.rs-3999289/v1
,2024, Model-Free Local Recalibration of Neural Networks,
,2022, A correlated pseudo-marginal approach to doubly intractable problems, , http://arxiv.org/abs/2210.02734v1
,2022, Modularized Bayesian analyses and cutting feedback in likelihood-free inference, , http://dx.doi.org/10.48550/arxiv.2203.09782
,2021, An Introduction to Quantum Computing for Statisticians and Data Scientists, , http://dx.doi.org/10.48550/arxiv.2112.06587
,2021, A new model of unreported COVID-19 cases outperforms three known epidemic-growth models in describing data from Cuba and Spain, , http://dx.doi.org/10.1101/2021.06.29.21259707
,2021, Modelling age-related changes in executive functions of soccer players, , http://arxiv.org/abs/2105.01226v1
,2020, Hidden Group Time Profiles: Heterogeneous Drawdown Behaviours in Retirement, , http://arxiv.org/abs/2009.01505v2
,2020, Likelihood-based inference for modelling packet transit from thinned flow summaries, , http://dx.doi.org/10.48550/arxiv.2008.13424
,2020, Stressor equivalents: A framework to prevent perverse outcomes in data-poor systems, , http://dx.doi.org/10.22541/au.159283264.49749008
,2019, Logistic regression models for aggregated data, , http://dx.doi.org/10.48550/arxiv.1912.03805
,2019, Multiclass classification of growth curves using random change points and heterogeneous random effects, , http://arxiv.org/abs/1909.07550v1
,