| Fast distributed consensus seeking in large-scale and high-density multi-agent systems with connectivity maintenance G Xie, H Xu, Y Li, X Hu, CD Wang Information Sciences 608, 1010-1028, 2022 | 6 | 2022 |
| Consensus enhancement for multi-agent systems with rotating-segmentation perception G Xie, H Xu, Y Li, X Hu, CD Wang Applied Intelligence 53 (5), 5750-5765, 2023 | 5 | 2023 |
| Simoun: Synergizing Interactive Motion-appearance Understanding for Vision-based Reinforcement Learning Y Huang, P Peng, Y Zhao, Y Zhai, H Xu, Y Tian 2023 IEEE/CVF International Conference on Computer Vision (ICCV), 176-185, 2023 | 1 | 2023 |
| Consensus seeking in large-scale multiagent systems with hierarchical switching-backbone topology G Xie, H Xu, Y Li, CD Wang, B Zhong, X Hu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 1 | 2023 |
| Hierarchical adaptive value estimation for multi-modal visual reinforcement learning Y Huang, P Peng, Y Zhao, H Xu, M Geng, Y Tian Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Connectivity-preserving rendezvous in discrete-time multi-agent systems via relative neighborhood proximity graph G Xie, B Zhong, H Xu, Y Li, X Hu, CD Wang Transactions of the Institute of Measurement and Control 46 (4), 771-784, 2024 | | 2024 |
| Density-Adaptive Model Based on Motif Matrix for Multi-Agent Trajectory Prediction D Wen, H Xu, Z He, Z Wu, G Tan, P Peng Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning H Xu, P Peng, G Tan, Y Li, X Xu, Y Tian Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Reinforcement Learning-Based Consensus Reaching in Large-Scale Social Networks S Guo, H Xu, G Xie, D Wen, Y Huang, P Peng International Conference on Neural Information Processing, 169-183, 2023 | | 2023 |
| Supplementary Material for “Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning” Y Huang, P Peng, Y Zhao, H Xu, M Geng, Y Tian | | |
Xianbiao (XB) HuPenn State UniversityVerified email at psu.edu
