| Causalvae: Disentangled representation learning via neural structural causal models M Yang, F Liu, Z Chen, X Shen, J Hao, J Wang CVPR 2021: Proceedings of the IEEE/CVF conference on computer vision and …, 2021 | 213 | 2021 |
| Top-N Recommendation with Counterfactual User Preference Simulation M Yang*, Q Dai*, Z Dong, X Chen, X He, J Wang CIKM 2021: Proceedings of the 30th ACM International Conference on …, 2021 | 46 | 2021 |
| Causalvae: Structured causal disentanglement in variational autoencoder M Yang, F Liu, Z Chen, X Shen, J Hao, J Wang arXiv preprint arXiv:2004.08697, 2020 | 28 | 2020 |
| Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation M Yang, Q Li, Z Qin, J Ye WWW 2020: Proceedings of the web conference 2020, 292-302, 2020 | 15 | 2020 |
| Chessgpt: Bridging policy learning and language modeling X Feng, Y Luo, Z Wang, H Tang, M Yang, K Shao, D Mguni, Y Du, J Wang NeurIPS 2023, 2024 | 11 | 2024 |
| Causal World Models by Unsupervised Deconfounding of Physical Dynamics M Li*, M Yang*, F Liu, X Chen, Z Chen, J Wang arXiv preprint arXiv:2012.14228, 2020 | 7 | 2020 |
| Lending Interaction Wings to Recommender Systems with Plug-and-Play Conversational Agents J Jin, X Chen, F Ye, M Yang, Y Feng, W Zhang, Y Yu, J Wang NeurIPS 2023, 2023 | 5* | 2023 |
| Rectifying Unfairness in Recommendation Feedback Loop M Yang, J Wang, JF Ton SIGIR 2023: Proceedings of the 46th International ACM SIGIR Conference on …, 2023 | 5 | 2023 |
| Debiased Recommendation with User Feature Balancing M Yang, G Cai, J Jin, Z Dong, X He, J Hao, S Weiqi, J Wang, X Chen ACM TOIS: ACM Transactions on Information Systems, 2022 | 5 | 2022 |
| Specify Robust Causal Representation from Mixed Observations M Yang, X Cai, F Liu, W Zhang, J Wang SIGKDD 2023: Proceedings of the 29th ACM SIGKDD Conference on Knowledge …, 2023 | 4 | 2023 |
| Deconfounding Representation Learning Based on User Interactions in Recommendation Systems J Gao, M Yang, Y Liu, J Li PAKDD2021, 2021 | 4 | 2021 |
| Invariant Learning via Probability of Sufficient and Necessary Causes M Yang, Z Fang, Y Zhang, Y Du, JF Ton, J Wang NeurIPS 2023 (Spotlight), 2024 | 2 | 2024 |
| Generalizable information theoretic causal representation M Yang, X Cai, F Liu, X Chen, Z Chen, J Hao, J Wang arXiv preprint arXiv:2202.08388, 2022 | 1 | 2022 |
| Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank J Jin, X Chen, W Zhang, M Yang, Y Wang, Y Du, Y Yu, J Wang CIKM 2023: Proceedings of the 32nd ACM International Conference on …, 2023 | | 2023 |
| Learning Scalable Causal Discovery Policies with Adversarial Reinforcement Learning X Cai, M Yang, Y Deng, F Liu, M Zhao, B An | | 2023 |
| InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization J Jin, Z He, M Yang, W Zhang, Y Yu, J Wang, J McAuley WWW 2024, 2023 | | 2023 |
| Manage Your Plug-in Data for Language Models: A Data-Centric Approach J Jin, Y Wu, M Yang, X He, W Zhang, Y Yang, Y Yu, J Wang | | 2023 |
| Informative Robust Causal Representation for Generalizable Deep Learning M Yang, F Liu, X Chen, Z Chen, HAO Jianye, J Wang | | 2021 |
| Parsimonious Demonstrations and Fine-Tuning for Large Language Models J Jin, Y Wu, M Yang, X He, W Zhang, Y Yang, Y Yu, J Wang | | |
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
