Assessing Classifier Fairness with Collider Bias. - Zhenlong Xu; Ziqi Xu 001; Jixue Liu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ke Wang 001 (PAKDD (2), 2022)

Causal Inference with Conditional Instruments Using Deep Generative Models. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le (AAAI, 2023)

Disentangled Representation for Causal Mediation Analysis. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Ke Wang 001 (AAAI, 2023)

Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference. - Debo Cheng; Yang Xie; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Yinghao Zhang; Zaiwen Feng (ICDM, 2023)

Disentangled Representation with Causal Constraints for Counterfactual Fairness. - Ziqi Xu 001; Jixue Liu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ke Wang 001 (PAKDD (1), 2023)

Learning Conditional Instrumental Variable Representation for Causal Effect Estimation. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Thuc Duy Le; Jixue Liu (ECML/PKDD (1), 2023)

A Data-Driven Approach to Finding K for K Nearest Neighbor Matching in Average Causal Effect Estimation. - Tingting Xu; Yinghao Zhang; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Debo Cheng; Zaiwen Feng (WISE, 2023)

Linking a predictive model to causal effect estimation. - Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Ha Xuan Tran; Thuc Duy Le; Jixue Liu (CoRR, 2023)

Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Kui Yu (CoRR, 2023)

Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Wentao Gao; Thuc Duy Le (AAAI, 2024)

TSI: A Multi-view Representation Learning Approach for Time Series Forecasting. - Wentao Gao; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le; Debo Cheng; Yanchang Zhao; Yun Chen 010 (AI (1), 2024)

Conditional Instrumental Variable Regression with Representation Learning for Causal Inference. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le (ICLR, 2024)

Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Kui Yu (ICLR, 2024)

Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables. - Yang Xie; Ziqi Xu 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Yinghao Zhang; Zaiwen Feng (CoRR, 2024)

Linking Model Intervention to Causal Interpretation in Model Explanation. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Kui Yu; Thuc Duy Le; Jixue Liu (CoRR, 2024)

Deconfounding Time Series Forecasting. - Wentao Gao; Feiyu Yang; Mengze Hong; Xiaojing Du; Zechen Hu; Xiongren Chen; Ziqi Xu 001 (CoRR, 2024)

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Thuc Duy Le; Xudong Guo; Shichao Zhang 001 (CoRR, 2024)

Cultural Bias Matters: A Cross-Cultural Benchmark Dataset and Sentiment-Enriched Model for Understanding Multimodal Metaphors. - Senqi Yang; Dongyu Zhang 001; Jing Ren 001; Ziqi Xu 001; Xiuzhen Zhang 001; Yiliao Song; Hongfei Lin; Feng Xia 001 (ACL (1), 2025)

PUB: An LLM-Enhanced Personality-Driven User Behaviour Simulator for Recommender System Evaluation. - Chenglong Ma; Ziqi Xu 001; Yongli Ren; Danula Hettiachchi; Jeffrey Chan (SIGIR, 2025)

Off-policy Evaluation for Multiple Actions in the Presence of Unobserved Confounders. - Haolin Wang 003; Lin Liu 003; Jiuyong Li; Ziqi Xu 001; Jixue Liu; Zehong Cao; Debo Cheng (WWW, 2025)

Fairness Evaluation with Item Response Theory. - Ziqi Xu 001; Sevvandi Kandanaarachchi; Cheng Soon Ong; Eirini Ntoutsi (WWW, 2025)

Towards Better Evaluation of Recommendation Algorithms with Bi-directional Item Response Theory. - Ziqi Xu 001; Chenglong Ma; Yongli Ren; Jeffrey Chan; Wei Shao 006; Feng Xia 001 (WWW (Companion Volume), 2025)

An Item Response Theory-based R module for Algorithm Portfolio Analysis. - Brodie Oldfield; Sevvandi Kandanaarachchi; Ziqi Xu 001; Mario Andrés Muñoz (SoftwareX, 2025)

Data-driven learning optimal K values for K-nearest neighbour matching in causal inference. - Yinghao Zhang; Tingting Xu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Zaiwen Feng (Data Min. Knowl. Discov., 2025)

Deconfounding representation learning for mitigating latent confounding effects in recommendation. - Guixian Zhang; Guan Yuan; Debo Cheng; Lin Liu 003; Jiuyong Li; Ziqi Xu 001; Shichao Zhang 001 (Knowl. Inf. Syst., 2025)

FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction. - Sichen Zhao; Wei Shao 006; Jeffrey Chan; Ziqi Xu 001; Flora Salim (CoRR, 2025)

Revisiting Pre-processing Group Fairness: A Modular Benchmarking Framework. - Brodie Oldfield; Ziqi Xu 001; Sevvandi Kandanaarachchi (CoRR, 2025)

Disentangled Representation Learning for Causal Inference With Instruments. - Debo Cheng; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Weijia Zhang 001; Jixue Liu; Thuc Duy Le (IEEE Trans. Neural Networks Learn. Syst., 2025)