Scott A. Sisson

Orcid: 0000-0001-8943-067X

Affiliations:
  • University of New South Wales, School of Mathematics and Statistics, Sydney, NSW, Australia
  • Bristol University, UK (PhD 2002)


According to our database1, Scott A. Sisson authored at least 48 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
Model-Free Local Recalibration of Neural Networks.
CoRR, 2024

2023
New models for symbolic data analysis.
Adv. Data Anal. Classif., September, 2023

Modularized Bayesian analyses and cutting feedback in likelihood-free inference.
Stat. Comput., February, 2023

Hawkes Processes With Stochastic Exogenous Effects for Continuous-Time Interaction Modelling.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Free-Form Variational Inference for Gaussian Process State-Space Models.
Proceedings of the International Conference on Machine Learning, 2023

2022
Likelihood-Based Inference for Modelling Packet Transit From Thinned Flow Summaries.
IEEE Trans. Signal Inf. Process. over Networks, 2022

Smoothing graphons for modelling exchangeable relational data.
Mach. Learn., 2022

Efficient Bayesian Synthetic Likelihood With Whitening Transformations.
J. Comput. Graph. Stat., 2022

2021
Logistic Regression Models for Aggregated Data.
J. Comput. Graph. Stat., 2021

Decoupling Sparsity and Smoothness in Dirichlet Belief Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Continuous-time edge modelling using non-parametric point processes.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Bayesian Nonparametric Space Partitions: A Survey.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures.
IEEE Trans. Signal Process., 2020

Composite likelihood methods for histogram-valued random variables.
Stat. Comput., 2020

Likelihood-free approximate Gibbs sampling.
Stat. Comput., 2020

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

Recurrent Dirichlet Belief Networks for Interpretable Dynamic Relational Data Modelling.
CoRR, 2020

Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Online Binary Space Partitioning Forests.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator.
IEEE Trans. Image Process., 2019

Scalable Deep Generative Relational Models with High-Order Node Dependence.
CoRR, 2019

Binary Space Partitioning Forests.
CoRR, 2019

Acceleration of expensive computations in Bayesian statistics using vector operations.
CoRR, 2019

Scalable Deep Generative Relational Model with High-Order Node Dependence.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variance reduction properties of the reparameterization trick.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Binary Space Partitioning Forest.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Variational Bayes with synthetic likelihood.
Stat. Comput., 2018

Recalibration: A post-processing method for approximate Bayesian computation.
Comput. Stat. Data Anal., 2018

Likelihood-free inference in high dimensions with synthetic likelihood.
Comput. Stat. Data Anal., 2018

On some variance reduction properties of the reparameterization trick.
CoRR, 2018

Rectangular Bounding Process.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The Binary Space Partitioning-Tree Process.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Nonlinear manifold representation in natural systems: The SOMersault.
Environ. Model. Softw., 2017

Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model.
Comput. Stat. Data Anal., 2017

2016
A dimension range representation (DRR) measure for self-organizing maps.
Pattern Recognit., 2016

Functional regression approximate Bayesian computation for Gaussian process density estimation.
Comput. Stat. Data Anal., 2016

2015
Increasing dependence on foreign water resources? An assessment of trends in global virtual water flows using a self-organizing time map.
Ecol. Informatics, 2015

Bayesian threshold selection for extremal models using measures of surprise.
Comput. Stat. Data Anal., 2015

2014
Simultaneous adjustment of bias and coverage probabilities for confidence intervals.
Comput. Stat. Data Anal., 2014

2012
On sequential Monte Carlo, partial rejection control and approximate Bayesian computation.
Stat. Comput., 2012

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in <i>Mycobacterium tuberculosis</i>.
PLoS Comput. Biol., 2012

Efficient hydrological model parameter optimization with Sequential Monte Carlo sampling.
Environ. Model. Softw., 2012

Likelihood-free Bayesian inference for α-stable models.
Comput. Stat. Data Anal., 2012

2010
Bayesian symbol detection in wireless relay networks via likelihood-free inference.
IEEE Trans. Signal Process., 2010

2009
Automating and evaluating reversible jump MCMC proposal distributions.
Stat. Comput., 2009

2007
A distance-based diagnostic for trans-dimensional Markov chains.
Stat. Comput., 2007

2003
Principles of Data Mining.
Inf. Retr., 2003


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