Principles of Data Mining. - Scott A. Sisson (Inf. Retr., 2003)

A distance-based diagnostic for trans-dimensional Markov chains. - Scott A. Sisson; Yanan Fan (Stat. Comput., 2007)

Automating and evaluating reversible jump MCMC proposal distributions. - Yanan Fan; Gareth W. Peters; Scott A. Sisson (Stat. Comput., 2009)

Bayesian symbol detection in wireless relay networks via likelihood-free inference. - Gareth W. Peters; Ido Nevat; Scott A. Sisson; Yanan Fan; Jinhong Yuan (IEEE Trans. Signal Process., 2010)

Likelihood-free Bayesian inference for α-stable models. - Gareth W. Peters; Scott A. Sisson; Yanan Fan (Comput. Stat. Data Anal., 2012)

Efficient hydrological model parameter optimization with Sequential Monte Carlo sampling. - Erwin Jeremiah; Scott A. Sisson; Ashish Sharma 002; Lucy A. Marshall (Environ. Model. Softw., 2012)

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis. - R. Zachariah Aandahl; Josephine F. Reyes; Scott A. Sisson; Mark M. Tanaka (PLoS Comput. Biol., 2012)

On sequential Monte Carlo, partial rejection control and approximate Bayesian computation. - Gareth W. Peters; Yanan Fan; Scott A. Sisson (Stat. Comput., 2012)

Simultaneous adjustment of bias and coverage probabilities for confidence intervals. - Patricia Menéndez; Yanan Fan; Paul H. Garthwaite; Scott A. Sisson (Comput. Stat. Data Anal., 2014)

Bayesian threshold selection for extremal models using measures of surprise. - J. Lee; Yanan Fan; Scott A. Sisson (Comput. Stat. Data Anal., 2015)

Increasing dependence on foreign water resources? An assessment of trends in global virtual water flows using a self-organizing time map. - Stephanie R. Clark; Peter Sarlin; Ashish Sharma 002; Scott A. Sisson (Ecol. Informatics, 2015)

Functional regression approximate Bayesian computation for Gaussian process density estimation. - G. S. Rodrigues; David J. Nott; Scott A. Sisson (Comput. Stat. Data Anal., 2016)

A dimension range representation (DRR) measure for self-organizing maps. - Stephanie R. Clark; Scott A. Sisson; Ashish Sharma 002 (Pattern Recognit., 2016)

Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model. - Jialiang Li 001; David J. Nott; Y. Fan; Scott A. Sisson (Comput. Stat. Data Anal., 2017)

Nonlinear manifold representation in natural systems: The SOMersault. - Stephanie R. Clark; Scott A. Sisson; Ashish Sharma 002 (Environ. Model. Softw., 2017)

The Binary Space Partitioning-Tree Process. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2018)

Rectangular Bounding Process. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (NeurIPS, 2018)

On some variance reduction properties of the reparameterization trick. - Ming Xu 015; Matias Quiroz; Robert Kohn; Scott A. Sisson (CoRR, 2018)

Likelihood-free inference in high dimensions with synthetic likelihood. - Victor M. H. Ong; David J. Nott; Minh-Ngoc Tran; Scott A. Sisson; Christopher C. Drovandi (Comput. Stat. Data Anal., 2018)

Recalibration: A post-processing method for approximate Bayesian computation. - G. S. Rodrigues; Dennis Prangle; Scott A. Sisson (Comput. Stat. Data Anal., 2018)

Variational Bayes with synthetic likelihood. - Victor M. H. Ong; David J. Nott; Minh-Ngoc Tran; Scott A. Sisson; Christopher C. Drovandi (Stat. Comput., 2018)

Binary Space Partitioning Forest. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2019)

Variance reduction properties of the reparameterization trick. - Ming Xu 015; Matias Quiroz; Robert Kohn; Scott A. Sisson (AISTATS, 2019)

Scalable Deep Generative Relational Model with High-Order Node Dependence. - Xuhui Fan 001; Bin Li 015; Caoyuan Li; Scott A. Sisson; Ling Chen 006 (NeurIPS, 2019)

Acceleration of expensive computations in Bayesian statistics using vector operations. - David J. Warne; Scott A. Sisson; Christopher C. Drovandi (CoRR, 2019)

Binary Space Partitioning Forests. - Xuhui Fan 001; Bin Li 015; Scott Anthony Sisson (CoRR, 2019)

Scalable Deep Generative Relational Models with High-Order Node Dependence. - Xuhui Fan 001; Bin Li 015; Scott Anthony Sisson; Caoyuan Li; Ling Chen 006 (CoRR, 2019)

Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator. - Caoyuan Li; Hong-Bo Xie; Xuhui Fan 001; Richard Yi Da Xu; Sabine Van Huffel; Scott A. Sisson; Kerrie L. Mengersen (IEEE Trans. Image Process., 2019)

Online Binary Space Partitioning Forests. - Xuhui Fan 001; Bin Li 015; Scott A. Sisson (AISTATS, 2020)

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Zheng Yu; Scott A. Sisson (IJCAI, 2020)

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (CoRR, 2020)

Predicting seagrass decline due to cumulative stressors. - 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 (Environ. Model. Softw., 2020)

Likelihood-free approximate Gibbs sampling. - G. S. Rodrigues; David J. Nott; Scott A. Sisson (Stat. Comput., 2020)

Composite likelihood methods for histogram-valued random variables. - Thomas Whitaker; Boris Beranger; Scott A. Sisson (Stat. Comput., 2020)

Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures. - Caoyuan Li; Hong-Bo Xie; Kerrie L. Mengersen; Xuhui Fan 001; Richard Yi Da Xu; Scott A. Sisson; Sabine Van Huffel (IEEE Trans. Signal Process., 2020)

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks. - Xuhui Fan 001; Bin Li 015; Yaqiong Li; Scott A. Sisson (ICML, 2021)

Bayesian Nonparametric Space Partitions: A Survey. - Xuhui Fan 001; Bin Li 015; Ling Luo 002; Scott A. Sisson (IJCAI, 2021)

Continuous-time edge modelling using non-parametric point processes. - Xuhui Fan 001; Bin Li 015; Feng Zhou 011; Scott A. Sisson (NeurIPS, 2021)

Decoupling Sparsity and Smoothness in Dirichlet Belief Networks. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (ECML/PKDD (2), 2021)

Logistic Regression Models for Aggregated Data. - Thomas Whitaker; Boris Beranger; Scott A. Sisson (J. Comput. Graph. Stat., 2021)

Efficient Bayesian Synthetic Likelihood With Whitening Transformations. - Jacob W. Priddle; Scott A. Sisson; David T. Frazier; Ian W. Turner; Christopher C. Drovandi (J. Comput. Graph. Stat., 2022)

Smoothing graphons for modelling exchangeable relational data. - Yaqiong Li; Xuhui Fan 001; Ling Chen 006; Bin Li 015; Scott A. Sisson (Mach. Learn., 2022)

Likelihood-Based Inference for Modelling Packet Transit From Thinned Flow Summaries. - Prosha Rahman; Boris Beranger; Scott A. Sisson; Matthew Roughan (IEEE Trans. Signal Inf. Process. over Networks, 2022)

Free-Form Variational Inference for Gaussian Process State-Space Models. - Xuhui Fan 001; Edwin V. Bonilla; Terence J. O'Kane; Scott A. Sisson (ICML, 2023)

Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling. - Xuhui Fan 001; Yaqiong Li; Ling Chen 006; Bin Li 015; Scott A. Sisson (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Modularized Bayesian analyses and cutting feedback in likelihood-free inference. - Atlanta Chakraborty; David J. Nott; Christopher C. Drovandi; David T. Frazier; Scott A. Sisson (Stat. Comput., 2023)

New models for symbolic data analysis. - Boris Beranger; Huan Lin; Scott A. Sisson (Adv. Data Anal. Classif., 2023)

Model-Free Local Recalibration of Neural Networks. - R. Torres; David J. Nott; Scott A. Sisson; T. Rodrigues; J. G. Reis; G. S. Rodrigues (CoRR, 2024)

Positional Encoder Graph Quantile Neural Networks for Geographic Data. - William E. R. de Amorim; Scott A. Sisson; T. Rodrigues; David J. Nott; Guilherme S. Rodrigues (CoRR, 2024)

Modelling time series with temporal and spatial correlations in transport planning using hierarchical ARIMA-copula Model: A Bayesian approach. - Siroos Shahriari; Scott A. Sisson; Taha Rashidi (Expert Syst. Appl., 2025)

Compact Bayesian Neural Networks via pruned MCMC sampling. - Ratneel Deo; Scott A. Sisson; Jody M. Webster; Rohitash Chandra (CoRR, 2025)