PROGRAM PRESENTATIONS

Please find below the program presentations received:

Keynote Presentations:

Antonietta Mira

Tutorial/ Keynote presentation: Bayesian dimensionality reduction via identifications of data intrinsic dimensions: theory and applications

Mira BOB_ID

Sudipto Banerjee

Keynote presentation: High-dimensional Bayesian Geostatistics (on your laptop!)

Tutorial: Geostatistical modelling and data analysis in R.  Banjeree html

Renate Meyer

Keynote presentation: Helping to unlock the secrets of the universe: from a statistical autopsy of black hole mergers to Bayesian nonparametric time series analysis

Tutorial:Go Nonparametric?! BNPtutorial-codes

Nial Friel

Tutorial: An Introduction to Statistical network analysis

Keynote presentation: Recent advances in the statistical analysis of network data

Invited Speakers:

Heikki Haario: Statistics for chaos and random patterns

Mark Briers: Alan Turing, Bayes, and model selection

                      Tutorial: Big Data: tools and statistical methods

Jegar Pitchforth: Taking the Commercial path: A case study in the early career experience for Statisticians

Benoit Liquet: Leverage pleiotropic effects from genome-wide association studies using both frequentist and Bayesian sparse group models

Invited Presentations:

Frank Tuyl: Objectively speaking, the Jeffreys prior for the binomial is not objective

Aminath Shausan: Minimising Dengue Spread by Transmissible Interfering Particles

Weichang Yu: Doubly-sparse Bayesian Discriminant Analysis for High Dimensional Data

Rodney Strachan: Reducing the State Space Dimension in a Large TVP-VAR

Matias Quiroz: Gaussian variational inference for spatio-temporal models

Nalan Basturk: Drivers of Success: A Bayesian state space approach to disentangling driver and car effects in Formula 1

Valentina Di Marco: Sequential Importance Sampling With Corrections For Partially Observed States

Minh-Ngoc Tran: Variational Bayes on Manifolds

Paul Brown: Modifications to LDS-based marginalisation methods for integrated nested Laplace approximations

Zarina Vakhitova: Victim Impact From and Self-Protective Behaviours against Different Types of Cyber Abuse

Matt Moores: Statistics from Mars: Bayesian signal processing for Raman spectroscopy

Daniela Vasco: Minding the uncertainty via prior calibration of testing items in Bayesian item response theory models

Julie Vercelloni: A multivariate hierarchical model to forecast changes in coral reef composition

Poster Session 1             Monday 25th November 2019

Presenter Title
Jose Romeo (Pepe) Modelling alcohol-consumption in New Zealand: A Bayesian conditional copula-based regression approach ROMEO
Chaitanya Joshi New classes of priors inspired by Approximate Bayesian Computation (ABC)
Kouji Yamamoto New test for comparing predictive values in the Bayesian method
Rory Ellis Using Bayesian Growth Models to Predict Grape Yield
Etienne Auclair Data-based approaches for seagrass meadow monitoring : learning the biomass of Zostera noltei in Aracachon’s bay using machine learning and dynamic Bayesian network.
Clara Grazian A Hierarchical Bayesian Spatio-Temporal Model to Estimate the Short-term Effects of Air Pollution on Human Health
Martin Ingramm Multi-output Gaussian Process Models for Species Distribution Modelling
John Xie (Gang Xie) Modelling complex systems with Bayesian Networks using Netica
Marcus Triplett Statistical models for optical recordings of neural circuits
Jacinta Holloway Beta distributions for better forest monitoring: combining random forest algorithms and Bayesian principles to interpolate missing data in satellite images.
Farzana Jahan Bayesian Empirical Likelihood Spatial Model applying Leroux Structure JAHAN
Ziwen An BSL: An R Package for Bayesian Synthetic Likelihood
Hayden Moffat Cost Effective Experiments in Ecology via Sequential Design
Aswi Evaluating the interplay between clusters, climatic covariates and spatial priors in spatio-temporal modelling of dengue in Makassar, Indonesia ASWI
Pubudu Thilan Optimisation of coral reef monitoring using Bayesian adaptive design methods
Hongbo Xie Bayesian nonnegative matrix factorization with Dirichlet process mixtures
Matthew Rushworth Bayesian Hierarchical Modelling of Caribbean Reefs
Jessica Cameron Projecting the future burden of cancer using Bayesian age-period-cohort models CAMERON

Poster Session 2             Tuesday 26th November 2019

Presenter Title
Catriona Ryan Bayesian Anomaly Detection for Streaming Advanced Manufacturing data RYAN
Viacheslav Lyubchich Complementing the power of deep learning with novel predictors and statistical model fusion
Patrick Graham Bayesian dual systems population estimation adjusting for linkage error and covariate misclassification. GRAHAM
Kouji Tahata On estimators of multinomial parameters using bayesian approach
James Tin Lok Ng Weighted Stochastic Block Model
Yoshifumi Ukita A Study on Simultaneous Experiments for Related Linear Models based on an Orthonormal System UKITA
Kairi Suzuki Optimal Estimating of the Magnitude of the change for Sources with Piecewise Constant Parameters under Bayesian Criterion
Laurence Davies Particle Filter Methods for Non-Linear and Chaotic SDEs
Win Wah Influence of Individual- And Area-Level Characteristics on Geographic Variation in Non-Small Cell Lung Cancer Mortality
Johanna Bayer Developing a Bayesian model to estimate multi-scanner effects in neuroimaging data within a machine learning framework
Ruben Loaiza-Maya Focused Bayesian Predicition.
Joshua Bon Delayed-acceptance sequential Monte Carlo: Optimising computational efficiency on the fly
Ethan Goan Improving Variational Inference for Bayesian Neural Networks GOAN
Jacob Priddle Efficient Bayesian synthetic likelihood with whitening transformations
Patricia Gilholm Identifying latent subgroups of children with developmental delay using Bayesian sequential updating and Dirichlet process mixture modelling
Imke Botha Particle Methods for Stochastic Differential Equation Mixed Effects Models BOTHA
Earl Duncan Comparing spatial models in the presence of spatial smoothing DUNCAN
Dan Li Efficient Bayesian estimation for GARCH-type models via Sequential Monte Carlo LI
Paul Wu Observational Uncertainty in Bayesian Networks and State Space Models WU

We would like to acknowledge and thank our sponsors for this event:

  • Bayesian Statistics Section of the Statistical Society of Australia. (SSA)
  • ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS)
  • Queensland University of Technology (QUT)
  • Bayesian Research & Applications Group (BRAG)
  • Australasian Chapter of the International Society for Bayesian Analysis (ISBA)
  • 4am Software Pty Ltd (4am Software Pty Ltd)