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Publications

Year Authors Title
  2024 Jennifer Scott, Arthur White, Cathal Walsh, Louis Aslett, Matthew A Rutherford, James Ng, Conor Judge, Kuruvilla Sebastian, S... Computable phenotype for real-world, data-driven retrospective identification of relapse in ANCA-associated vasculitis RMD Open, 10(2), pp1-11. DOI: http://dx.doi.org/10.1136/rmdopen-2023-003962
  2023 Tin Lok James Ng Penalized maximum likelihood estimator for mixture of von Mises¿Fisher distributions Metrika. DOI: http://dx.doi.org/10.1007/s00184-022-00867-0
  2023 Tin Lok James Ng, Andrew Zammit-Mangion Tin Lok James Ng [PDF] from projecteuclid.org Non-homogeneous Poisson process intensity modeling and estimation using measure transport Bernoulli. DOI: http://dx.doi.org/10.3150/22-BEJ1480
  2023 Z Zhao, TLJ Ng Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 14174, pp460-476
  2022 Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos van Geffen, Michiel van Weele, Anto... The association between ambient UVB dose and ANCA-associated vasculitis relapse and onset Arthritis Research & Therapy, 24(1), pp1-14. DOI: https://doi.org/10.1186/s13075-022-02834-6
  2022 Tin Lok James Ng, Andrew Zammit-Mangion Spherical Poisson point process intensity function modeling and estimation with measure transport Spatial Statistics. DOI: http://dx.doi.org/10.1016/j.spasta.2022.100629
  2022 Daniel E Zoughbie, Tin Lok James Ng, Jacqueline Y Thompson, Kathleen T Watson, Rami Farraj, Eric L Ding Ramadan fasting and weight change trajectories: Time-varying association of weight during and after Ramadan in low-income and refugee populations . DOI: http://dx.doi.org/10.1371/journal.pgph.0000371
  2021 Tin Lok James Ng; Kwok-Kun Kwong Universal approximation on the hypersphere Communications in Statistics - Theory and Methods
  2021 Andrew Zammit-Mangion, Tin Lok James Ng, Quan Vu, Maurizio Filippone Deep compositional spatial models Journal of the American Statistical Association
  2021 Tin Lok James Ng; Thomas Brendan Murphy Weighted stochastic block model Statistical Methods & Applications
  2021 Jake Thompson; James Ng; Bruce Armstrong; Eleonora Feletto; Tam Ha Differences in colorectal cancer (CRC) patients who did and did not undergo screening: Results from the 45 and Up Study cohort Cancer Epidemiology, 72
  2021 Tin Lok James Ng, Thomas Brendan Murphy, Ted Westling, Tyler H. McCormick, Bailey K. Fosdick Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmode Annals of Applied Statistics
  2021 Tin Lok James Ng; Thomas Brendan Murphy Model-based Clustering of Count Processes Journal of Classification volume, 38, pp188-211
  2021 Tin Lok James Ng; Thomas Brendan Murphy Model-based clustering for random hypergraphs Advances in Data Analysis and Classification
  2020 Linyi Yang, Eoin M. Kenny, Tin Lok Ng, Yi Yang, Barry Smyth, and Ruihai Dong Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification THE 28TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS
  2020 Linyi Yang, Tin Lok James Ng, Barry Smyth, Riuhai Dong Html: Hierarchical transformer-based multi-task learning for volatility prediction Proceedings of The Web Conference
  2019 Tin Lok James Ng, Thomas Brendan Murphy Generalized Random Dot Product graph Statistics & Probability Letters, 148, pp143-149
  2019 Bailey K. Fosdick; Tyler H. McCormick; Thomas Brendan Murphy; Tin Lok James Ng; Ted Westling Multiresolution Network Models Journal of Computational and Graphical Statistics, 28(1), pp185-196
  2019 Tin Lok J. Ng; Thomas B. Murphy Estimation of the intensity function of an inhomogeneous Poisson process with a change-point The Canadian Journal of Statistics, 47, pp604-618
  2017 Linyi Yang, Tin Lok James Ng, Catherine Mooney, Ruihai Dong Multi-level attention-based neural networks for distant supervised relation extraction 25th Irish Conference on Artificial Intelligence and Cognitive Science

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