| 2025 | ICDM | Neural Autoregressive Flows for Markov Boundary Learning. | Khoa Nguyen, Bao Duong, Viet Huynh, Thin Nguyen |
| 2025 | ICLR | Causal Discovery via Bayesian Optimization. | Bao Duong, Sunil Gupta, Thin Nguyen |
| 2025 | ICML | Identifying Causal Direction via Variational Bayesian Compression. | Quang-Duy Tran, Bao Duong, Phuoc Nguyen, Thin Nguyen |
| 2025 | PAKDD | Amortized Conditional Independence Testing. | Bao Duong, Nu Hoang, Thin Nguyen |
| 2024 | ECAI | Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows. | Nu Hoang, Bao Duong, Thin Nguyen |
| 2024 | ECAI | Scalable Variational Causal Discovery Unconstrained by Acyclicity. | Nu Hoang, Bao Duong, Thin Nguyen |
| 2024 | WACV | Domain Generalisation via Risk Distribution Matching. | Toan Nguyen, Kien Do, Bao Duong, Thin Nguyen |
| 2024 | SDM | Robust Estimation of Causal Heteroscedastic Noise Models. | Quang-Duy Tran, Bao Duong, Phuoc Nguyen, Thin Nguyen |
| 2023 | AAAI | Diffeomorphic Information Neural Estimation. | Bao Duong, Thin Nguyen |
| 2023 | ECAI | Heteroscedastic Causal Structure Learning. | Bao Duong, Thin Nguyen |
| 2023 | ICDM | Differentiable Bayesian Structure Learning with Acyclicity Assurance. | Quang-Duy Tran, Phuoc Nguyen, Bao Duong, Thin Nguyen |
| 2023 | KDD | Causal Inference via Style Transfer for Out-of-distribution Generalisation. | Toan Nguyen, Kien Do, Duc Thanh Nguyen, Bao Duong, Thin Nguyen |
| 2022 | ACIIDS | Efficient Classification with Counterfactual Reasoning and Active Learning. | Azhar Mohammed, Dang Nguyen, Bao Duong, Thin Nguyen |
| 2022 | ADMA | Handling Missing Data with Markov Boundary. | Azhar Mohammed, Dang Nguyen, Bao Duong, Melanie Nichols, Thin Nguyen |
| 2022 | ICDM | Conditional Independence Testing via Latent Representation Learning. | Bao Duong, Thin Nguyen |
| 2022 | IJCNN | Causality-aided Recommendation Systems. | Tri Minh Nguyen, Azhar Mohammed, Bao Duong, Thin Nguyen |