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ORCIDScott A. Sisson
Person information
- affiliation: University of New South Wales, School of Mathematics and Statistics, Sydney, NSW, Australia
- affiliation (PhD 2002): Bristol University, UK
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Journal Articles
- 2023
[j30]Boris Beranger
, Huan Lin, Scott A. Sisson:
New models for symbolic data analysis. Adv. Data Anal. Classif. 17(3): 659-699 (2023)- [j29]Xuhui Fan, Yaqiong Li, Ling Chen, Bin Li, Scott A. Sisson:
Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1848-1861 (2023) - [j28]Atlanta Chakraborty, David J. Nott, Christopher C. Drovandi, David T. Frazier, Scott A. Sisson:
Modularized Bayesian analyses and cutting feedback in likelihood-free inference. Stat. Comput. 33(1): 33 (2023) - 2022
- [j27]Jacob W. Priddle, Scott A. Sisson, David T. Frazier, Ian W. Turner, Christopher C. Drovandi:
Efficient Bayesian Synthetic Likelihood With Whitening Transformations. J. Comput. Graph. Stat. 31(1): 50-63 (2022) - [j26]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Smoothing graphons for modelling exchangeable relational data. Mach. Learn. 111(1): 319-344 (2022) - [j25]Prosha Rahman, Boris Beranger, Scott A. Sisson, Matthew Roughan:
Likelihood-Based Inference for Modelling Packet Transit From Thinned Flow Summaries. IEEE Trans. Signal Inf. Process. over Networks 8: 571-583 (2022) - 2021
- [j24]Thomas Whitaker, Boris Beranger, Scott A. Sisson:
Logistic Regression Models for Aggregated Data. J. Comput. Graph. Stat. 30(4): 1049-1067 (2021) - 2020
- [j23]Matthew P. Adams, Edwin J. Y. Koh, Maria P. Vilas, Catherine J. Collier, Victoria M. Lambert, Scott A. Sisson, Matias Quiroz, Eve McDonald-Madden, Len J. McKenzie, Katherine R. O'Brien:
Predicting seagrass decline due to cumulative stressors. Environ. Model. Softw. 130: 104717 (2020) - [j22]G. S. Rodrigues, David J. Nott, Scott A. Sisson:
Likelihood-free approximate Gibbs sampling. Stat. Comput. 30(4): 1057-1073 (2020) - [j21]Thomas Whitaker, Boris Beranger, Scott A. Sisson:
Composite likelihood methods for histogram-valued random variables. Stat. Comput. 30(5): 1459-1477 (2020) - [j20]Caoyuan Li, Hong-Bo Xie, Kerrie L. Mengersen, Xuhui Fan, Richard Yi Da Xu, Scott A. Sisson, Sabine Van Huffel:
Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures. IEEE Trans. Signal Process. 68: 3860-3870 (2020) - 2019
- [j19]Caoyuan Li, Hong-Bo Xie, Xuhui Fan, Richard Yi Da Xu, Sabine Van Huffel, Scott A. Sisson, Kerrie L. Mengersen:
Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator. IEEE Trans. Image Process. 28(10): 4899-4911 (2019) - 2018
- [j18]G. S. Rodrigues, Dennis Prangle, Scott A. Sisson:
Recalibration: A post-processing method for approximate Bayesian computation. Comput. Stat. Data Anal. 126: 53-66 (2018) - [j17]Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi:
Likelihood-free inference in high dimensions with synthetic likelihood. Comput. Stat. Data Anal. 128: 271-291 (2018) - [j16]Victor M. H. Ong, David J. Nott, Minh-Ngoc Tran, Scott A. Sisson, Christopher C. Drovandi:
Variational Bayes with synthetic likelihood. Stat. Comput. 28(4): 971-988 (2018) - 2017
- [j15]Jialiang Li, David J. Nott, Y. Fan, Scott A. Sisson:
Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model. Comput. Stat. Data Anal. 106: 77-89 (2017) - [j14]Stephanie R. Clark, Scott A. Sisson, Ashish Sharma:
Nonlinear manifold representation in natural systems: The SOMersault. Environ. Model. Softw. 89: 61-76 (2017) - 2016
- [j13]G. S. Rodrigues, David J. Nott, Scott A. Sisson:
Functional regression approximate Bayesian computation for Gaussian process density estimation. Comput. Stat. Data Anal. 103: 229-241 (2016) - [j12]Stephanie R. Clark, Scott A. Sisson, Ashish Sharma:
A dimension range representation (DRR) measure for self-organizing maps. Pattern Recognit. 53: 276-286 (2016) - 2015
- [j11]J. Lee, Yanan Fan, Scott A. Sisson:
Bayesian threshold selection for extremal models using measures of surprise. Comput. Stat. Data Anal. 85: 84-99 (2015) - [j10]Stephanie R. Clark, Peter Sarlin, Ashish Sharma, Scott A. Sisson:
Increasing dependence on foreign water resources? An assessment of trends in global virtual water flows using a self-organizing time map. Ecol. Informatics 26(2): 192-202 (2015) - 2014
- [j9]Patricia Menéndez, Yanan Fan, Paul H. Garthwaite, Scott A. Sisson:
Simultaneous adjustment of bias and coverage probabilities for confidence intervals. Comput. Stat. Data Anal. 70: 35-44 (2014) - 2012
- [j8]Gareth W. Peters, Scott A. Sisson, Yanan Fan:
Likelihood-free Bayesian inference for α-stable models. Comput. Stat. Data Anal. 56(11): 3743-3756 (2012) - [j7]Erwin Jeremiah, Scott A. Sisson, Ashish Sharma, Lucy Marshall:
Efficient hydrological model parameter optimization with Sequential Monte Carlo sampling. Environ. Model. Softw. 38: 283-295 (2012) - [j6]R. Zachariah Aandahl, Josephine F. Reyes, Scott A. Sisson, Mark M. Tanaka:
A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis. PLoS Comput. Biol. 8(6) (2012) - [j5]Gareth W. Peters, Yanan Fan, Scott A. Sisson:
On sequential Monte Carlo, partial rejection control and approximate Bayesian computation. Stat. Comput. 22(6): 1209-1222 (2012) - 2010
- [j4]Gareth W. Peters, Ido Nevat, Scott A. Sisson, Yanan Fan, Jinhong Yuan:
Bayesian symbol detection in wireless relay networks via likelihood-free inference. IEEE Trans. Signal Process. 58(10): 5206-5218 (2010) - 2009
- [j3]Yanan Fan, Gareth W. Peters, Scott A. Sisson:
Automating and evaluating reversible jump MCMC proposal distributions. Stat. Comput. 19(4): 409-421 (2009) - 2007
- [j2]Scott A. Sisson, Yanan Fan:
A distance-based diagnostic for trans-dimensional Markov chains. Stat. Comput. 17(4): 357-367 (2007) - 2003
- [j1]Scott A. Sisson:
Principles of Data Mining. Inf. Retr. 6(2): 275-277 (2003)
Conference and Workshop Papers
- 2023
- [c12]Xuhui Fan, Edwin V. Bonilla, Terence J. O'Kane, Scott A. Sisson:
Free-Form Variational Inference for Gaussian Process State-Space Models. ICML 2023: 9603-9622 - 2021
- [c11]Xuhui Fan, Bin Li, Yaqiong Li, Scott A. Sisson:
Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks. ICML 2021: 3068-3077 - [c10]Xuhui Fan, Bin Li, Ling Luo, Scott A. Sisson:
Bayesian Nonparametric Space Partitions: A Survey. IJCAI 2021: 4408-4415 - [c9]Xuhui Fan, Bin Li, Feng Zhou, Scott A. Sisson:
Continuous-time edge modelling using non-parametric point processes. NeurIPS 2021: 2319-2330 - [c8]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Decoupling Sparsity and Smoothness in Dirichlet Belief Networks. ECML/PKDD (2) 2021: 148-163 - 2020
- [c7]Xuhui Fan, Bin Li, Scott A. Sisson:
Online Binary Space Partitioning Forests. AISTATS 2020: 527-537 - [c6]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Zheng Yu, Scott A. Sisson:
Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling. IJCAI 2020: 2470-2476 - 2019
- [c5]Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson:
Variance reduction properties of the reparameterization trick. AISTATS 2019: 2711-2720 - [c4]Xuhui Fan, Bin Li, Scott A. Sisson:
Binary Space Partitioning Forest. AISTATS 2019: 3022-3031 - [c3]Xuhui Fan, Bin Li, Caoyuan Li, Scott A. Sisson, Ling Chen:
Scalable Deep Generative Relational Model with High-Order Node Dependence. NeurIPS 2019: 12637-12647 - 2018
- [c2]Xuhui Fan, Bin Li, Scott A. Sisson:
The Binary Space Partitioning-Tree Process. AISTATS 2018: 1859-1867 - [c1]Xuhui Fan, Bin Li, Scott A. Sisson:
Rectangular Bounding Process. NeurIPS 2018: 7631-7641
Informal and Other Publications
- 2024
- [i12]R. Torres, David J. Nott, Scott A. Sisson, T. Rodrigues, J. G. Reis, G. S. Rodrigues:
Model-Free Local Recalibration of Neural Networks. CoRR abs/2403.05756 (2024) - 2023
- [i11]Xuhui Fan, Edwin V. Bonilla, Terence J. O'Kane, Scott A. Sisson:
Free-Form Variational Inference for Gaussian Process State-Space Models. CoRR abs/2302.09921 (2023) - 2020
- [i10]Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling. CoRR abs/2002.10235 (2020) - [i9]Xuhui Fan, Yaqiong Li, Ling Chen, Bin Li, Scott A. Sisson:
Smoothing Graphons for Modelling Exchangeable Relational Data. CoRR abs/2002.11159 (2020) - [i8]Xuhui Fan, Bin Li, Ling Luo, Scott A. Sisson:
Bayesian Nonparametric Space Partitions: A Survey. CoRR abs/2002.11394 (2020) - [i7]Xuhui Fan, Bin Li, Scott A. Sisson:
Online Binary Space Partitioning Forests. CoRR abs/2003.00269 (2020) - 2019
- [i6]David J. Warne, Scott A. Sisson, Christopher C. Drovandi:
Acceleration of expensive computations in Bayesian statistics using vector operations. CoRR abs/1902.09046 (2019) - [i5]Xuhui Fan, Bin Li, Scott Anthony Sisson:
Rectangular Bounding Process. CoRR abs/1903.03906 (2019) - [i4]Xuhui Fan, Bin Li, Scott Anthony Sisson:
The Binary Space Partitioning-Tree Process. CoRR abs/1903.09343 (2019) - [i3]Xuhui Fan, Bin Li, Scott Anthony Sisson:
Binary Space Partitioning Forests. CoRR abs/1903.09348 (2019) - [i2]Xuhui Fan, Bin Li, Scott Anthony Sisson, Caoyuan Li, Ling Chen:
Scalable Deep Generative Relational Models with High-Order Node Dependence. CoRR abs/1911.01535 (2019) - 2018
- [i1]Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson:
On some variance reduction properties of the reparameterization trick. CoRR abs/1809.10330 (2018)
Coauthor Index
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