Select Publications
Journal articles
2009, 'Smaller projected increases in 20-year temperature returns over Australia in skill-selected climate models', Geophysical Research Letters, 36, pp. L06710, http://dx.doi.org/10.1029/2009GL037293
,2009, 'The epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis', Proceedings of the National Academy of Sciences of the United States of America, 106, pp. 14711 - 14715, http://dx.doi.org/10.1073/pnas.0902437106
,2009, 'Towards automating model selection for a mark-recapture-recovery analysis', Journal of the Royal Statistical Society Series C - Applied Statistics, 58, pp. 247 - 266
,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
,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 the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, Honolulu, HI, United States, pp. 9603 - 9622, presented at 40th International Conference on Machine Learning (ICML 2023), Honolulu, HI, United States, 23 July 2023, https://proceedings.mlr.press/v202/fan23a.html
,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 Wallach H; Larochelle H; Beygelzimer A; d'Alche-Buc F; Fox E; Garnett R (eds.), NeurIPS 2019, 33rd Conference on Neural INformation Processing Systems 2019, NEURAL INFORMATION PROCESSING SYSTEMS (NIPS), Vancouver, Canada, presented at NeurIPS 2019, Vancouver, Canada, 08 December 2019 - 14 December 2019
,2019, 'Binary space partitioning forests', in Chaudhuri K; Sugiyama M (ed.), AISTATS 2019, Proceedings of Machine Learning Research, MICROTOME PUBLISHING, Naha, Okinawa, Japan, presented at AISTATS 2019, Naha, Okinawa, Japan, 16 April 2019 - 18 April 2019, http://proceedings.mlr.press/v89/fan19b/fan19b.pdf
,2018, 'Rectangular bounding process', in Bengio S; Wallach H; Larochelle H; Grauman K; CesaBianchi N; Garnett R (eds.), NeurIPS 2018, 32nd Conference on Neural Information Processing Systems, NEURAL INFORMATION PROCESSING SYSTEMS (NIPS), Montreal, pp. 7620 - 7630, 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 Storkey A; PerezCruz F (ed.), 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, http://dx.doi.org/10.26190/unsworks/28191, 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, Positional Encoder Graph Quantile Neural Networks for Geographic Data, http://dx.doi.org/10.48550/arxiv.2409.18865
,2024, Calibrated Multivariate Regression with Localized PIT Mappings, http://dx.doi.org/10.48550/arxiv.2409.10855
,2024, Analysing symbolic data by pseudo-marginal methods, http://arxiv.org/abs/2408.04419v1
,2024, Flexible max-stable processes for fast and efficient inference, http://arxiv.org/abs/2407.13958v4
,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, http://dx.doi.org/10.48550/arxiv.2403.05756
,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
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