26 citations · 31 across the 16 of their papers we have counts for
16 papers
A Sparse-Group Pliable Lasso
Mohammad Javad Davoudabadi, Minh Long Nguyen, Amirhossein Ghatari +2
The sparse-group pliable Lasso (SGPL) extends the pliable Lasso and group pliable Lasso by combining sparse-group regularization with a predictor-level coupling penalty, enabling s…
Geographic Characterisation of Children's Health and Wellbeing through Vulnerability Indices Using Principal Component Analysis (PCA) and K-Means Clustering
Harriette Phillips, Aiden Price, Kerrie Mengersen
Using Australian children as a case study, this paper aims to develop vulnerability indices to characterise the health and well-being of children aged 0-5 years old. The indices ar…
AIMSCheck: Leveraging LLMs for AI-Assisted Review of Modern Slavery Statements Across Jurisdictions
Adriana Eufrosina Bora, Akshatha Arodi, Duoyi Zhang +6
Modern Slavery Acts mandate that corporations disclose their efforts to combat modern slavery, aiming to enhance transparency and strengthen practices for its eradication. However,…
A Principled Approach to Bayesian Transfer Learning
Adam Bretherton, Joshua J. Bon, David J. Warne +2
Updating information given some observed data is the core tenet of Bayesian inference. Bayesian transfer learning extends this idea by incorporating information…
Unsupervised anomaly detection in spatio-temporal stream network sensor data
Edgar Santos-Fernandez, Jay M. Ver Hoef, Erin E. Peterson +6
The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are…
Bayesian spatiotemporal modelling of political violence and conflict events using discrete-time Hawkes processes
Raiha Browning, Hamish Patten, Judith Rousseau +1
The monitoring of conflict risk in the humanitarian sector is largely based on simple historic averages. The overarching goal of this work is to assess the potential for using a mo…
Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations
Conor Hassan, Joshua J Bon, Elizaveta Semenova +2
Federated learning (FL) allows for collaborative model training across decentralized clients while preserving privacy by avoiding data sharing. However, current FL methods assume c…
Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference
Conor Hassan, Matthew Sutton, Antonietta Mira +1
Vertical federated learning (VFL) has emerged as a paradigm for collaborative model estimation across multiple clients, each holding a distinct set of covariates. This paper introd…
Guidelines for the Creation of Analysis Ready Data
Harriette Phillips, Aiden Price, Owen Forbes +4
Globally, there is an increased need for guidelines to produce high-quality data outputs for analysis. No framework currently exists that provides guidelines for a comprehensive ap…
Proposer selection in EIP-7251
Sandra Johnson, Kerrie Mengersen, Patrick O'Callaghan +1
Immediate settlement, or single-slot finality (SSF), is a long-term goal for Ethereum. The growing active validator set size is placing an increasing computational burden on the ne…
Creating a Spatial Vulnerability Index for Environmental Health
Aiden Price, Kerrie Mengersen, Michael Rigby +1
Extreme natural hazards are increasing in frequency and intensity. These natural changes in our environment, combined with man-made pollution, have substantial economic, social and…
Creating area level indices of behaviours impacting cancer in Australia with a Bayesian generalised shared component model
James Hogg, Susanna Cramb, Jessica Cameron +2
This study develops a model-based index creation approach called the Generalized Shared Component Model (GSCM) by drawing on the large field of factor models. The proposed fully Ba…
Spatial Non-parametric Bayesian Clustered Coefficients
Wala Draidi Areed, Aiden Price, Helen Thompson +2
In the field of population health research, understanding the similarities between geographical areas and quantifying their shared effects on health outcomes is crucial. In this pa…
Bayesian Cluster Geographically Weighted Regression for Spatial Heterogeneous Data
Wala Draidi Areed, Aiden Price, Helen Thompson +3
Spatial statistical models are commonly used in geographical scenarios to ensure spatial variation is captured effectively. However, spatial models and cluster algorithms can be co…
A Two-Stage Bayesian Small Area Estimation Approach for Proportions
James Hogg, Jessica Cameron, Susanna Cramb +2
With the rise in popularity of digital Atlases to communicate spatial variation, there is an increasing need for robust small-area estimates. However, current small-area estimation…
A Survey of Bayesian Statistical Approaches for Big Data
Farzana Jahan, Insha Ullah, Kerrie L Mengersen
The modern era is characterised as an era of information or Big Data. This has motivated a huge literature on new methods for extracting information and insights from these data. A…