Multi-level Attention-Based Neural Networks for Distant Supervised Relation Extraction. - Linyi Yang; Tin Lok James Ng; Catherine Mooney; Ruihai Dong (AICS, 2017)

Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification. - Linyi Yang; Eoin M. Kenny; Tin Lok James Ng; Yi Yang 042; Barry Smyth; Ruihai Dong (COLING, 2020)

HTML: Hierarchical Transformer-based Multi-task Learning for Volatility Prediction. - Linyi Yang; Tin Lok James Ng; Barry Smyth; Ruihai Dong (WWW, 2020)

Model-based Clustering of Count Processes. - Tin Lok James Ng; Thomas Brendan Murphy (J. Classif., 2021)

Posterior Regularisation on Bayesian Hierarchical Mixture Clustering. - Weipéng Huáng; Tin Lok James Ng; Nishma Laitonjam; Neil J. Hurley (CoRR, 2021)

Fact Check: Analyzing Financial Events from Multilingual News Sources. - Linyi Yang; Tin Lok James Ng; Barry Smyth; Ruihai Dong (CoRR, 2021)

Model-based clustering for random hypergraphs. - Tin Lok James Ng; Thomas Brendan Murphy (Adv. Data Anal. Classif., 2022)

Fair Machine Learning with Structured and Unstructured Features: A Case Study in Mortality Prediction. - Hanyang Chen; Zhouting Zhao; Tin Lok James Ng (AICS, 2023)

Fairness-Aware Processing Techniques in Survival Analysis: Promoting Equitable Predictions. - Zhouting Zhao; Tin Lok James Ng (ECML/PKDD (6), 2023)

A Generalized Bayesian Approach to Distribution-on-Distribution Regression. - Tin Lok James Ng (UAI, 2024)

Mixture modeling with normalizing flows for spherical density estimation. - Tin Lok James Ng; Andrew Zammit-Mangion (Adv. Data Anal. Classif., 2024)