Causality Learning: A New Perspective for Interpretable Machine Learning. - Guandong Xu; Tri Dung Duong; Qian Li 003; Shaowu Liu; Xianzhi Wang 001 (CoRR, 2020)

Causal-Aware Generative Imputation for Automated Underwriting. - Qian Li 003; Tri Dung Duong; Zhichao Wang 001; Shaowu Liu; Dingxian Wang; Guandong Xu (CIKM, 2021)

Stochastic Intervention for Causal Effect Estimation. - Tri Dung Duong; Qian Li 003; Guandong Xu (IJCNN, 2021)

Prototype-based Counterfactual Explanation for Causal Classification. - Tri Dung Duong; Qian Li 003; Guandong Xu (CoRR, 2021)

Stochastic intervention for causal inference via reinforcement learning. - Tri Dung Duong; Qian Li 003; Guandong Xu (Neurocomputing, 2022)

CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data Using Normalizing Flows. - Tri Dung Duong; Qian Li 003; Guandong Xu (PAKDD (2), 2023)

Achieving counterfactual fairness with imperfect structural causal model. - Tri Dung Duong; Qian Li 003; Guandong Xu (Expert Syst. Appl., 2024)

Causality-based counterfactual explanation for classification models. - Tri Dung Duong; Qian Li 003; Guandong Xu (Knowl. Based Syst., 2024)