| LIIR: Learning individual intrinsic reward in multi-agent reinforcement learning Y Du, L Han, M Fang, T Dai, J Liu, D Tao Advances in Neural Information Processing Systems (NeurIPS) 32, 4403-4414, 2019 | 168 | 2019 |
| Curriculum-guided hindsight experience replay M Fang, T Zhou, Y Du, L Han, Z Zhang Advances in Neural Information Processing Systems (NeurIPS), 2019 | 158 | 2019 |
| A review of safe reinforcement learning: Methods, theory and applications S Gu, L Yang, Y Du, G Chen, F Walter, J Wang, Y Yang, A Knoll arXiv preprint arXiv:2205.10330, 2022 | 144 | 2022 |
| Learning Correlated Communication Topology in Multi-Agent Reinforcement Learning Y Du, B Liu, V Moens, Z Liu, Z Ren, J Wang, X Chen, H Zhang AAMAS, 2021 | 57 | 2021 |
| Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL R Yang, Y Lu, W Li, H Sun, M Fang, Y Du, X Li, L Han, C Zhang ICLR, 2022 | 55 | 2022 |
| Safe multi-agent reinforcement learning for multi-robot control S Gu, JG Kuba, Y Chen, Y Du, L Yang, A Knoll, Y Yang Artificial Intelligence 319, 103905, 2023 | 54* | 2023 |
| Grid-wise control for multi-agent reinforcement learning in video game ai Y Du*, L Han*, P Sun*, J Xiong, Q Wang, X Sun, H Liu, T Zhang International Conference on Machine Learning (ICML), 2576-2585, 2019 | 51* | 2019 |
| Ordering-Based Causal Discovery with Reinforcement Learning X Wang, Y Du, S Zhu, L Ke, Z Chen, J Hao, J Wang IJCAI, 2021 | 50 | 2021 |
| Reinforcement Learning with Multiple Relational Attention for Solving Vehicle Routing Problems Y Xu, M Fang, L Chen, G Xu, Y Du, C Zhang IEEE Transactions on Cybernetics (TCYB), 2021 | 50 | 2021 |
| Enhancing the robustness of neural collaborative filtering systems under malicious attacks Y Du, M Fang, J Yi, C Xu, J Cheng, D Tao IEEE Transactions on Multimedia 21 (3), 555-565, 2018 | 48 | 2018 |
| Learning in Nonzero-Sum Stochastic Games with Potentials D Mguni, Y Wu, Y Du, Y Yang, Z Wang, M Li, Y Wen, J Jennings, J Wang ICML, 2021 | 47 | 2021 |
| Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games Y Xu*, M Fang*, L Chen, Y Du, JT Zhou, C Zhang Advances in Neural Information Processing Systems (NeurIPS) 33, 2020 | 39 | 2020 |
| GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning J Ruan, Y Du, X Xiong, D Xing, X Li, L Meng, H Zhang, J Wang, B Xu AAMAS 2022, 2022 | 33 | 2022 |
| Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning R Liu, F Bai, Y Du, Y Yang Advances in Neural Information Processing Systems, 2022 | 29 | 2022 |
| Towards query efficient black-box attacks: An input-free perspective Y Du, M Fang, J Yi, J Cheng, D Tao Proceedings of the 11th ACM CCS@Workshop on Artificial Intelligence and …, 2018 | 23 | 2018 |
| MHER: Model-based hindsight experience replay R Yang, M Fang, L Han, Y Du, F Luo, X Li arXiv preprint arXiv:2107.00306, 2021 | 21 | 2021 |
| Privileged matrix factorization for collaborative filtering Y Du, C Xu, D Tao IJCAI International Joint Conference on Artificial Intelligence, 2017 | 17 | 2017 |
| Generalization in Text-based Games via Hierarchical Reinforcement Learning Y Xu, M Fang, L Chen, Y Du, C Zhang Findings of EMNLP, 2021 | 14 | 2021 |
| Reinforcement Recommendation with User Multi-aspect Preference X Chen, Y Du, L Xia, J Wang The Web Conference (TheWebConf), 2021 | 14 | 2021 |
| Perceiving the World: Question-guided Reinforcement Learning for Text-based Games Y Xu, M Fang, L Chen, Y Du, JT Zhou, C Zhang ACL 2022, 2022 | 12 | 2022 |
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
