Search Results for author: Kerrie Mengersen

Found 14 papers, 6 papers with code

Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations

no code implementations25 May 2024 Conor Hassan, Joshua J Bon, Elizaveta Semenova, Antonietta Mira, Kerrie Mengersen

We demonstrate the SIGMA prior's effectiveness on synthetic data and showcase its utility in a real-world example of FL for spatial data, using a conditional autoregressive prior to model spatial dependence across Australia.

Decision Making Epidemiology +2

Scalable Vertical Federated Learning via Data Augmentation and Amortized Inference

no code implementations7 May 2024 Conor Hassan, Matthew Sutton, Antonietta Mira, Kerrie Mengersen

Vertical federated learning (VFL) has emerged as a paradigm for collaborative model estimation across multiple clients, each holding a distinct set of covariates.

Bayesian Inference Data Augmentation +3

Dependent Cluster Mapping (DCMAP): Optimal clustering of directed acyclic graphs for statistical inference

no code implementations8 Aug 2023 Paul Pao-Yen Wu, Fabrizio Ruggeri, Kerrie Mengersen

A Directed Acyclic Graph (DAG) can be partitioned or mapped into clusters to support and make inference more computationally efficient in Bayesian Network (BN), Markov process and other models.

Clustering

Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis

no code implementations28 Jul 2023 Conor Hassan, Robert Salomone, Kerrie Mengersen

This article provides a comprehensive synthesis of the recent developments in synthetic data generation via deep generative models, focusing on tabular datasets.

Synthetic Data Generation

Assessing the Spatial Structure of the Association between Attendance at Preschool and Childrens Developmental Vulnerabilities in Queensland Australia

no code implementations25 May 2023 wala Draidi Areed, Aiden Price, Kathryn Arnett, Helen Thompson, Reid Malseed, Kerrie Mengersen

The research explores the influence of preschool attendance (one year before full-time school) on the development of children during their first year of school.

Graph Neural Network-Based Anomaly Detection for River Network Systems

1 code implementation19 Apr 2023 Katie Buchhorn, Edgar Santos-Fernandez, Kerrie Mengersen, Robert Salomone

We further examine the strengths and weaknesses of this baseline approach, GDN, in comparison to other benchmarking methods on complex real-world river network data.

Anomaly Detection Benchmarking +2

Piecewise Deterministic Markov Processes for Bayesian Neural Networks

2 code implementations17 Feb 2023 Ethan Goan, Dimitri Perrin, Kerrie Mengersen, Clinton Fookes

Inference on modern Bayesian Neural Networks (BNNs) often relies on a variational inference treatment, imposing violated assumptions of independence and the form of the posterior.

Variational Inference

Federated Variational Inference Methods for Structured Latent Variable Models

no code implementations7 Feb 2023 Conor Hassan, Robert Salomone, Kerrie Mengersen

Federated learning methods enable model training across distributed data sources without data leaving their original locations and have gained increasing interest in various fields.

Federated Learning Topic Models +1

A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning

no code implementations18 Jan 2023 Hong-Bo Xie, Caoyuan Li, Shuliang Wang, Richard Yi Da Xu, Kerrie Mengersen

Construction of dictionaries using nonnegative matrix factorisation (NMF) has extensive applications in signal processing and machine learning.

Dictionary Learning

clusterBMA: Bayesian model averaging for clustering

2 code implementations9 Sep 2022 Owen Forbes, Edgar Santos-Fernandez, Paul Pao-Yen Wu, Hong-Bo Xie, Paul E. Schwenn, Jim Lagopoulos, Lia Mills, Dashiell D. Sacks, Daniel F. Hermens, Kerrie Mengersen

In this work we introduce clusterBMA, a method that enables weighted model averaging across results from multiple unsupervised clustering algorithms.

Clustering Electroencephalogram (EEG) +1

On the intrinsic dimensionality of Covid-19 data: a global perspective

no code implementations8 Mar 2022 Abhishek Varghese, Edgar Santos-Fernandez, Francesco Denti, Antonietta Mira, Kerrie Mengersen

This paper aims to develop a global perspective of the complexity of the relationship between the standardised per-capita growth rate of Covid-19 cases, deaths, and the OxCGRT Covid-19 Stringency Index, a measure describing a country's stringency of lockdown policies.

Bayesian item response models for citizen science ecological data

1 code implementation16 Mar 2020 Edgar Santos-Fernandez, Kerrie Mengersen

We introduce a new methodological framework of item response and linear logistic test models with application to citizen science data used in ecology research.

Applications

A network flow approach to visualising the roles of covariates in random forests

2 code implementations27 Jun 2017 Benjamin R. Fitzpatrick, Kerrie Mengersen

Together these visualisations facilitate substantial insights into the roles of covariates in a random forest but do not communicate the frequencies of the hierarchies of covariates effects across the random forest or the orders in which covariates occur in these hierarchies.

Other Statistics

Computationally Efficient Simulation of Queues: The R Package queuecomputer

1 code implementation6 Mar 2017 Anthony Ebert, Paul Wu, Kerrie Mengersen, Fabrizio Ruggeri

Approximate Bayesian computation could offer a straight-forward way to infer parameters for such networks if we could simulate data quickly enough.

Computation Optimization and Control

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