16 citations · 28 across the 19 of their papers we have counts for
19 papers
Data-driven Linear Quadratic Tracking based Temperature Control of a Big Area Additive Manufacturing System
Eleni Zavrakli, Andrew Parnell, Andrew Dickson +1
Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing (AM), as various aspects of the AM process require continuous monitoring and regulation,…
SERT: A Transfomer Based Model for Spatio-Temporal Sensor Data with Missing Values for Environmental Monitoring
Amin Shoari Nejad, Rocío Alaiz-Rodríguez, Gerard D. McCarthy +3
Environmental monitoring is crucial to our understanding of climate change, biodiversity loss and pollution. The availability of large-scale spatio-temporal data from sources such…
Bayesian Causal Forests for Multivariate Outcomes: Application to Irish Data From an International Large Scale Education Assessment
Nathan McJames, Andrew Parnell, Yong Chen Goh +1
Bayesian Causal Forests (BCF) is a causal inference machine learning model based on a highly flexible non-parametric regression and classification tool called Bayesian Additive Reg…
Bayesian Additive Main Effects and Multiplicative Interaction Models using Tensor Regression for Multi-environmental Trials
Antonia A. L. Dos Santos, Danilo A. Sarti, Rafael A. Moral +1
We propose a Bayesian tensor regression model to accommodate the effect of multiple factors on phenotype prediction. We adopt a set of prior distributions that resolve identifiabil…
NEAL: An open-source tool for audio annotation
Anthony Gibbons, Ian Donohue, Courtney E. Gorman +2
Passive acoustic monitoring is used widely in ecology, biodiversity, and conservation studies. Data sets collected via acoustic monitoring are often extremely large and built to be…
Review of Clustering Methods for Functional Data
Mimi Zhang, Andrew Parnell
Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations. Application of functio…
vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models
Alan Inglis, Andrew Parnell, Catherine Hurley
We present vivid, an R package for visualizing variable importance and variable interactions in machine learning models. The package provides a range of displays including heatmap…
Visualizations for Bayesian Additive Regression Trees
Alan Inglis, Andrew Parnell, Catherine Hurley
Tree-based regression and classification has become a standard tool in modern data science. Bayesian Additive Regression Trees (BART) has in particular gained wide popularity due i…
Variational Inference for Additive Main and Multiplicative Interaction Effects Models
AntÔnia A. L. Dos Santos, Rafael A. Moral, Danilo A. Sarti +1
In plant breeding the presence of a genotype by environment (GxE) interaction has a strong impact on cultivation decision making and the introduction of new crop cultivars. The com…
Hierarchical Embedded Bayesian Additive Regression Trees
Bruna Wundervald, Andrew Parnell, Katarina Domijan
We propose a simple yet powerful extension of Bayesian Additive Regression Trees which we name Hierarchical Embedded BART (HE-BART). The model allows for random effects to be inclu…
GP-BART: a novel Bayesian additive regression trees approach using Gaussian processes
Mateus Maia, Keefe Murphy, Andrew C. Parnell
The Bayesian additive regression trees (BART) model is an ensemble method extensively and successfully used in regression tasks due to its consistently strong predictive performanc…
Inference for extreme spatial temperature events in a changing climate with application to Ireland
Dáire Healy, Jonathan Tawn, Peter Thorne +1
We investigate the changing nature of the frequency, magnitude and spatial extent of extreme temperatures in Ireland from 1931 to 2022. We develop an extreme value model that captu…
Bayesian Multi-Species N-Mixture Models for Unmarked Animal Communities
Niamh Mimnagh, Andrew Parnell, Estevao Prado +1
We propose an extension of the N-mixture model which allows for the estimation of both abundances of multiple species simultaneously and their inter-species correlations. We also p…
Accounting for shared covariates in semi-parametric Bayesian additive regression trees
Estevão B. Prado, Andrew C. Parnell, Keefe Murphy +3
We propose some extensions to semi-parametric models based on Bayesian additive regression trees (BART). In the semi-parametric BART paradigm, the response variable is approximated…
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models
Alan Inglis, Andrew Parnell, Catherine Hurley
Variable importance, interaction measures, and partial dependence plots are important summaries in the interpretation of statistical and machine learning models. In this paper we d…
Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing
Mimi Zhang, Andrew Parnell, Dermot Brabazon +1
Bayesian optimization (BO) is an approach to globally optimizing black-box objective functions that are expensive to evaluate. BO-powered experimental design has found wide applica…
Real-Time Anomaly Detection for Advanced Manufacturing: Improving on Twitter's State of the Art
Caitríona M. Ryan, Andrew Parnell, Catherine Mahoney
The detection of anomalies in real time is paramount to maintain performance and efficiency across a wide range of applications including web services and smart manufacturing. This…
An Evaluation of Methods for Real-Time Anomaly Detection using Force Measurements from the Turning Process
Yuanzhi Huang, Eamonn Ahearne, Szymon Baron +1
We examined the use of three conventional anomaly detection methods and assess their potential for on-line tool wear monitoring. Through efficient data processing and transformatio…
Prediction of tool-wear in turning of medical grade cobalt chromium molybdenum alloy (ASTM F75) using non-parametric Bayesian models
Damien McParland, Szymon Baron, Sarah O'Rourke +3
We present a novel approach to estimating the effect of control parameters on tool wear rates and related changes in the three force components in turning of medical grade Co-Cr-Mo…