• McInerney A and Burke K (2023). Feedforward neural networks as statistical models: Improving interpretability through uncertainty quantification. arXiv preprint arXiv:2311.08139. [preprint]
  • McInerney A and Burke K (2022). A Statistically-Based Approach to Feedforward Neural Network Model Selection. arXiv preprint arXiv:2207.04248. [preprint]
  • O'Neill M and Burke K (2022). Robust Distributional Regression with Automatic Variable Selection. arXiv preprint arXiv:2212.07317. [preprint]



  • O'Neill M and Burke K (2023). Variable selection using a smooth information criterion for distributional regression models. Statistics and Computing , 33(3), 71. [paper] [preprint]
  • Jaouimaa FZ, Ha ID and Burke K (2023) Penalized Variable Selection in Multi-Parameter Regression Survival Modelling. Statistical Methods in Medical Research. [paper] [preprint]
  • Kia A, Waterson J, Bargary N, Rolt S, Burke K, Robertson J, Garcia S, Benavoli A, Bergström D (2023). Determinants of Intravenous Infusion Longevity and Infusion Failure via a Nonlinear Model Analysis of Smart Pump Event Logs: Retrospective Study. Journal of Medical Internet Research (JMIR): Artificial Intelligence, 2, e48628. [paper]
  • Fennell SC, Gleeson JP, Quayle M, Durrheim K and Burke K (2023). Agent-based null models for examining experimental social interaction networks. Scientific Reports, 13(1), 5249. [paper] [preprint]
  • Dubovskaya A, Fennell SC, Burke K, Gleeson JP and O’Kiely D (2023). Analysis of mean-field approximation for Deffuant opinion dynamics on networks. SIAM Journal on Applied Mathematics, 83(2), pp.436-459. [paper] [preprint]
  • O’Mahony S, O’Donovan CB, Collins N, Burke K, Doyle G and Gibney ER  (2023). Reformulation of Processed Yogurt and Breakfast Cereals over Time: A Scoping Review. International Journal of Environmental Research and Public Health, 20(4), 3322. [paper]


  • Jaouimaa FZ, Ha ID and Burke K (2022). Multi-parameter regression survival modelling with random effects. Statistical Modelling. [paper] [preprint]
  • Yang Y, McClean S, Donnelly M, Burke K and Khan K (2022). A multi-components approach to monitoring process structure and customer behaviour concept drift. Expert Systems with Applications, 210, 118533. [paper]
  • Yang Y, McClean S, Donnelly M, Burke K and Khan K (2022). Detecting and responding to concept drift in business processes. Algorithms, 15(5), 174. [paper]


  • Jaouimaa FZ, Dempsey D, Van Osch S, Kinsella S, Burke K, Wyse J and Sweeney J (2021). An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost. PLOS ONE, 16(12), e0260632. [paper] [preprint]
  • Burke K and Patilea V (2021). A likelihood-based approach for cure regression models. TEST, 30(3), pp.693-712. [paper] [preprint]
  • Rizk J, Walsh C and Burke K (2021). An alternative formulation of Coxian phase‐type distributions with covariates: Application to emergency department length of stay. Statistics in Medicine, 40(6), pp.1574-1592. [paper] [preprint]
  • Fennell SC, Burke K, Quayle M and Gleeson JP (2021). Generalized mean-field approximation for the Deffuant opinion dynamics model on networks. Physical Review E, 103(1), 012314. [paper] [preprint]
  • Browne LD, Jaouimaa FZ, Walsh C, Perez-Ruiz F, Richette P, Burke K and Stack AG (2021). Serum uric acid and mortality thresholds among men and women in the Irish health system: A cohort study. European Journal of Internal Medicine, 84, pp.46-55. [paper]
  • O’Brien JD, Burke ME and Burke K (2021). A generalized framework for simultaneous long-short feedback trading. IEEE Transactions on Automatic Control, 66(6), pp.2652-2663. [paper] [preprint]
  • O’Brien JD, Burke K, Burke ME and Barmish BR (2021). A Generalization of the Classical Kelly Betting Formula to the Case of Temporal Correlation. IEEE Control Systems Letters, 5(2), pp.623-628. [paper] [preprint]
  • Fitzmaurice O, Walsh R and Burke K (2021). The ‘Mathematics Problem’and preservice post primary mathematics teachers–analysing 17 years of diagnostic test data. International Journal of Mathematical Education in Science and Technology, 52(2), pp.259-281. [paper]


  • Burke K, Jones MC and Noufaily A (2020). A flexible parametric modelling framework for survival analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics), 69(2), pp.429-457. [paper] [preprint]
  • Jones MC, Noufaily A and Burke K (2020). A bivariate power generalized Weibull distribution: a flexible parametric model for survival analysis. Statistical methods in medical research, 29(8), pp.2295-2306. [paper] [preprint]
  • Burke K, Eriksson F and Pipper CB (2020). Semiparametric multiparameter regression survival modeling. Scandinavian Journal of Statistics, 47(2), pp.555-571. [paper] [preprint]
  • Peng D, MacKenzie G and Burke K (2020). A multiparameter regression model for interval‐censored survival data. Statistics in medicine, 39(14), pp.1903-1918. [paper] [preprint]
  • MacCarron P, Maher PJ, Fennell S, Burke K, Gleeson JP, Durrheim K and Quayle M (2020). Agreement threshold on Axelrod’s model of cultural dissemination. PLOS ONE, 15(6), e0233995. [paper] [preprint]


  • Burke K and MacKenzie G (2017). Multi‐parameter regression survival modeling: An alternative to proportional hazards. Biometrics, 73(2), pp.678-686. [paper] [preprint]


  • McGrath O and Burke K (2021). Binomial confidence intervals for rare events: importance of defining margin of error relative to magnitude of proportion. arXiv preprint arXiv:2109.02516. [preprint]
  • Burke K and Barmish BR (2020). A Data-Driven Control-Theoretic Paradigm for Pandemic Mitigation with Application to Covid-19. arXiv preprint arXiv:2008.06347. [preprint]
  • Rizk J, Burke K and Walsh C (2019). On the non-uniqueness of representations of coxian phase-type distributions. arXiv preprint arXiv:1901.03849. [preprint]