| One-shot face reenactment using appearance adaptive normalization G Yao, Y Yuan, T Shao, S Li, S Liu, Y Liu, M Wang, K Zhou Proceedings of the AAAI conference on artificial intelligence 35 (4), 3172-3180, 2021 | 29 | 2021 |
| Self-play reinforcement learning with comprehensive critic in computer games S Liu, J Cao, Y Wang, W Chen, Y Liu Neurocomputing 449, 207-213, 2021 | 24 | 2021 |
| Learning communication for cooperation in dynamic agent-number environment W Liu, S Liu, J Cao, Q Wang, X Lang, Y Liu IEEE/ASME Transactions on Mechatronics 26 (4), 1846-1857, 2021 | 7 | 2021 |
| The Architecture of a Driverless Robot Car Based on EyeBot System S Sun, J Zheng, Z Qiao, S Liu, Z Lin, T Bräunl Journal of Physics: Conference Series 1267 (1), 012099, 2019 | 6 | 2019 |
| Learning multi-agent cooperation via considering actions of teammates S Liu, W Liu, W Chen, G Tian, J Chen, Y Tong, J Cao, Y Liu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 4 | 2023 |
| Moving forward in formation: a decentralized hierarchical learning approach to multi-agent moving together S Liu, L Wen, J Cui, X Yang, J Cao, Y Liu 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 4 | 2021 |
| True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning W Tan, W Zhang, S Liu, L Zheng, X Wang, B An The Twelfth International Conference on Learning Representations, 2023 | 2 | 2023 |
| Controlling type confounding in ad hoc teamwork with instance-wise teammate feedback rectification D Xing, P Gu, Q Zheng, X Wang, S Liu, L Zheng, B An, G Pan International Conference on Machine Learning, 38272-38285, 2023 | 2 | 2023 |
| True Knowledge Comes from Practice: Aligning LLMs with Embodied Environments via Reinforcement Learning W Tan, W Zhang, S Liu, L Zheng, X Wang, B An arXiv preprint arXiv:2401.14151, 2024 | 1 | 2024 |
| Hilonet: Hierarchical imitation learning from non-aligned observations S Liu, J Cao, W Chen, L Wen, Y Liu arXiv preprint arXiv:2011.02671, 2020 | 1 | 2020 |
| MCMC: Multi-Constrained Model Compression via One-Stage Envelope Reinforcement Learning S Li, J Chen, S Liu, C Zhu, G Tian, Y Liu IEEE Transactions on Neural Networks and Learning Systems, 2024 | | 2024 |
| Expert demonstrations guide reward decomposition for multi-agent cooperation L Weiwei, J Wei, L Shanqi, R Yudi, Z Kexin, Y Jiang, L Yong Neural Computing and Applications 35 (27), 19847-19863, 2023 | | 2023 |
| Multi-Agent Cooperation via Unsupervised Learning of Joint Intentions S Liu, W Liu, W Chen, G Tian, Y Liu arXiv preprint arXiv:2307.02200, 2023 | | 2023 |
| Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning S Liu, Y Hu, R Wu, D Xing, Y Xiong, C Fan, K Kuang, Y Liu arXiv preprint arXiv:2302.06872, 2023 | | 2023 |
| CICC: Channel Pruning via the Concentration of Information and Contributions of Channels. Y Chen, Z Li, Y Yang, L Xie, Y Liu, L Ma, S Liu, G Tian BMVC, 243, 2022 | | 2022 |
| Supplementary Material for CICC: Channel Pruning via the Concentration of Information and Contributions of Channels Y Chen, Z Li, Y Yang, L Xie, Y Liu, L Ma, S Liu, G Tian | | 2022 |
| Learning Intra-group Cooperation in Multi-agent Systems W Liu, S Liu, J Yang, Y Liu 2021 27th International Conference on Mechatronics and Machine Vision in …, 2021 | | 2021 |
| SOLVING HOMOGENEOUS AND HETEROGENEOUS CO-OPERATIVE TASKS WITH GREEDY SEQUENTIAL EXE S Liu, D Xing, P Gu, X Wang, B An, Y Liu | | |
Thomas BräunlProfessor in Electrical and Computer Engineering, The University of Western AustraliaVerified email at uwa.edu.au
