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ORCIDAndrew C. Parnell
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2020 – today
- 2025
[j22]Anthony Gibbons
, Francesco Martini, Cian White, Emma King, Jane C. Stout, Ian Donohue, Andrew Parnell:
ExActR: A Shiny app for creating ecosystem extent accounts. Ecol. Informatics 87: 103072 (2025)- [j21]Eleni Zavrakli, Andrew Parnell, Subhrakanti Dey:
Reinforcement Learning based temperature regulation for a Material Extrusion Additive Manufacturing system. IFAC J. Syst. Control. 33: 100330 (2025) - [j20]Alan Inglis, Andrew Parnell:
Permutation-based visualisation of input and encoded space in autoencoders. J. Data Sci. Stat. Vis. 5(2) (2025) - [j19]Eleni Zavrakli, Andrew Parnell, Andrew Dickson, Subhrakanti Dey:
Data-driven linear quadratic tracking based temperature control of a big area additive manufacturing system. J. Intell. Manuf. 36(7): 4549-4565 (2025) - [j18]André Felipe Berdusco Menezes, Andrew C. Parnell, Keefe Murphy:
Finite mixture representations of zero-and-N-inflated distributions for count-compositional data. J. Multivar. Anal. 210: 105492 (2025) - [j17]Maeve Upton, Andrew Parnell, Niamh Cahill:
reslr: An R Package for Relative Sea Level Modelling. R J. 16(2): 61-81 (2025) - [i17]Niamh Mimnagh, Andrew Parnell, Conor McAloon, Jaden Carlson, Maria Guelbenzu, Jonas Brock, Damien Barrett, Guy McGrath, Jamie Tratalos, Rafael A. Moral:
Predicting BVD Re-emergence in Irish Cattle From Highly Imbalanced Herd-Level Data Using Machine Learning Algorithms. CoRR abs/2504.13116 (2025) - 2024
- [j16]Mateus Maia, Keefe Murphy, Andrew C. Parnell:
GP-BART: A novel Bayesian additive regression trees approach using Gaussian processes. Comput. Stat. Data Anal. 190: 107858 (2024) - [j15]Amin Shoari Nejad, Rocío Alaíz-Rodríguez, Gerard D. McCarthy, Brian Kelleher, Anthony Grey, Andrew Parnell:
SERT: A transformer based model for multivariate temporal sensor data with missing values for environmental monitoring. Comput. Geosci. 188: 105601 (2024) - [j14]Alan Inglis, Andrew Parnell, Catherine Hurley:
Visualisations for Bayesian Additive Regression Trees. J. Data Sci. Stat. Vis. 4(1) (2024) - [i16]Rocío Alaíz-Rodríguez, Andrew C. Parnell:
An information theoretic approach to quantify the stability of feature selection and ranking algorithms. CoRR abs/2402.05295 (2024) - [i15]Alan Inglis, Andrew Parnell, Natarajan Subramani, Fiona Doohan:
Machine Learning Applied to the Detection of Mycotoxin in Food: A Review. CoRR abs/2404.15387 (2024) - [i14]Nathan McJames, Ann O'Shea, Andrew Parnell:
Bayesian Causal Forests for Longitudinal Data: Assessing the Impact of Part-Time Work on Growth in High School Mathematics Achievement. CoRR abs/2407.11927 (2024) - [i13]Anthony Gibbons, Emma King, Ian Donohue, Andrew Parnell:
Generative AI-based data augmentation for improved bioacoustic classification in noisy environments. CoRR abs/2412.01530 (2024) - 2023
- [j13]Alan Inglis, Andrew Parnell, Catherine Hurley:
vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models. R J. 15(2): 344-361 (2023) - [j12]Mimi Zhang, Andrew Parnell:
Review of Clustering Methods for Functional Data. ACM Trans. Knowl. Discov. Data 17(7): 91:1-91:34 (2023) - [c1]Eleni Zavrakli, Andrew Parnell, Subhrakanti Dey:
Output Feedback Reinforcement Learning for Temperature Control in a Fused Deposition Modelling Additive Manufacturing System. CoDIT 2023: 1483-1487 - [i12]Antônia A. L. Dos Santos, Danilo A. Sarti, Rafael A. Moral, Andrew C. Parnell:
Bayesian Additive Main Effects and Multiplicative Interaction Models using Tensor Regression for Multi-environmental Trials. CoRR abs/2301.03655 (2023) - [i11]Nathan McJames, Andrew C. Parnell, Yong Chen Goh, Ann O'Shea:
Bayesian Causal Forests for Multivariate Outcomes: Application to Irish Data From an International Large Scale Education Assessment. CoRR abs/2303.04874 (2023) - [i10]Amin Shoari Nejad, Rocío Alaíz-Rodríguez, Gerard D. McCarthy, Brian Kelleher, Anthony Grey, Andrew C. Parnell:
SERT: A Transfomer Based Model for Spatio-Temporal Sensor Data with Missing Values for Environmental Monitoring. CoRR abs/2306.03042 (2023) - 2022
- [j11]Alan Inglis, Andrew Parnell, Catherine B. Hurley:
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models. J. Comput. Graph. Stat. 31(3): 766-778 (2022) - [i9]Mateus Maia, Keefe Murphy, Andrew C. Parnell:
GP-BART: a novel Bayesian additive regression trees approach using Gaussian processes. CoRR abs/2204.02112 (2022) - [i8]Bruna D. Wundervald, Andrew C. Parnell, Katarina Domijan:
Hierarchical Embedded Bayesian Additive Regression Trees. CoRR abs/2204.07207 (2022) - [i7]Antônia A. L. Dos Santos, Rafael A. Moral, Danilo A. Sarti, Andrew C. Parnell:
Variational Inference for Additive Main and Multiplicative Interaction Effects Models. CoRR abs/2207.00011 (2022) - [i6]Anthony Gibbons, Ian Donohue, Courtney E. Gorman, Emma King, Andrew Parnell:
NEAL: An open-source tool for audio annotation. CoRR abs/2212.01457 (2022) - 2021
- [j10]Prerna Tewari, Eugene Kashdan, Cathal Walsh, Cara M. Martin, Andrew C. Parnell, John J. O'Leary:
Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling. PLoS Comput. Biol. 17(8) (2021) - [j9]Estevão B. Prado, Rafael A. Moral, Andrew C. Parnell:
Bayesian additive regression trees with model trees. Stat. Comput. 31(3): 20 (2021) - [i5]Mimi Zhang, Andrew Parnell, Dermot Brabazon, Alessio Benavoli:
Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing. CoRR abs/2107.12809 (2021) - [i4]Estevão B. Prado, Andrew C. Parnell, Nathan McJames, Ann O'Shea, Rafael A. Moral:
Semi-parametric Bayesian Additive Regression Trees. CoRR abs/2108.07636 (2021) - 2020
- [j8]Rocío Alaíz-Rodríguez, Andrew C. Parnell:
A Machine Learning Approach for Lamb Meat Quality Assessment Using FTIR Spectra. IEEE Access 8: 52385-52394 (2020) - [j7]Bruna D. Wundervald, Andrew C. Parnell, Katarina Domijan:
Generalizing Gain Penalization for Feature Selection in Tree-Based Models. IEEE Access 8: 190231-190239 (2020) - [j6]Gonzalo Molpeceres Barrientos, Rocío Alaíz-Rodríguez, Víctor González-Castro, Andrew C. Parnell:
Machine Learning Techniques for the Detection of Inappropriate Erotic Content in Text. Int. J. Comput. Intell. Syst. 13(1): 591-603 (2020) - [j5]Rocío Alaíz-Rodríguez, Andrew C. Parnell:
An information theoretic approach to quantify the stability of feature selection and ranking algorithms. Knowl. Based Syst. 195: 105745 (2020) - [i3]Estevão B. Prado, Rafael A. Moral, Andrew C. Parnell:
Bayesian Additive Regression Trees with Model Trees. CoRR abs/2006.07493 (2020) - [i2]Bruna D. Wundervald, Andrew C. Parnell, Katarina Domijan:
Generalizing Gain Penalization for Feature Selection in Tree-based Models. CoRR abs/2006.07515 (2020)
2010 – 2019
- 2019
- [j4]Damien McParland, Szymon Baron, Sarah O'Rourke, Denis Dowling, Eamonn Ahearne, Andrew Parnell:
Prediction of tool-wear in turning of medical grade cobalt chromium molybdenum alloy (ASTM F75) using non-parametric Bayesian models. J. Intell. Manuf. 30(3): 1259-1270 (2019) - 2018
- [j3]Emma Howard, Maria Meehan, Andrew Parnell:
Contrasting prediction methods for early warning systems at undergraduate level. Internet High. Educ. 37: 66-75 (2018) - [j2]Belinda Hernández, Adrian E. Raftery, Stephen R Pennington, Andrew C. Parnell:
Bayesian Additive Regression Trees using Bayesian model averaging. Stat. Comput. 28(4): 869-890 (2018) - [i1]Yuanzhi Huang, Eamonn Ahearne, Szymon Baron, Andrew Parnell:
An Evaluation of Methods for Real-Time Anomaly Detection using Force Measurements from the Turning Process. CoRR abs/1812.09178 (2018) - 2016
- [j1]Kevin C. Rue-Albrecht, Paul A. McGettigan, Belinda Hernández, Nicolas C. Nalpas, David A. Magee, Andrew C. Parnell, Stephen V. Gordon, David E. MacHugh:
GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data. BMC Bioinform. 17: 126 (2016)
Coauthor Index
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last updated on 2025-10-28 23:11 CET by the dblp team
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