| Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction C Yu*, X Ma*, J Ren, H Zhao, S Yi European Conference on Computer Vision (ECCV), 2020 | 317 | 2020 |
| Balanced meta-softmax for long-tailed visual recognition J Ren, C Yu, S Sheng, X Ma, H Zhao, S Yi, H Li Advances in Neural Information Processing Systems 33, 2020 | 293 | 2020 |
| Particle Filter Recurrent Neural Networks X Ma, P Karkus, D Hsu, WS Lee The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020 | 132* | 2020 |
| Differentiable algorithm networks for composable robot learning P Karkus, X Ma, D Hsu, LP Kaelbling, WS Lee, T Lozano-Pérez Robotics: Science and Systems (RSS), 2019 | 75* | 2019 |
| Learning latent graph dynamics for visual manipulation of deformable objects X Ma, D Hsu, WS Lee 2022 International Conference on Robotics and Automation (ICRA), 8266-8273, 2022 | 39* | 2022 |
| Contrastive Variational Model-Based Reinforcement Learning for Complex Observations X Ma, S Chen, D Hsu, WS Lee 4th Conference on Robot Learning (CoRL), 2020 | 33* | 2020 |
| Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations X Ma, P Karkus, D Hsu, WS Lee, N Ye International Conference on Learning Representations (ICLR), 2020 | 33 | 2020 |
| Beep: A bayesian perspective early stage event prediction model for online social networks X Ma, X Gao, G Chen 2017 IEEE International Conference on Data Mining (ICDM), 973-978, 2017 | 10 | 2017 |
| Ab Initio Particle-based Object Manipulation S Chen, X Ma, Y Lu, D Hsu Robotics: Science and Systems (RSS), 2021 | 7 | 2021 |
| Towards Overcoming False Positives in Visual Relationship Detection D Jin*, X Ma*, C Zhang, Y Zhou, J Tao, M Zhang, Zhoujun, X Li British Machine Vision Conference (BMVC), 2021 | 6 | 2021 |
| Predicting hot events in the early period through Bayesian model for social networks Z Zheng, X Gao, X Ma, G Chen IEEE Transactions on Knowledge and Data Engineering, 2020 | 6 | 2020 |
| Trust-based time series data model for mobile crowdsensing X Ma, Z Zheng, F Wu, G Chen 2017 IEEE International Conference on Communications (ICC), 1-6, 2017 | 5 | 2017 |
| Imitation Learning As State Matching via Differentiable Physics S Chen, X Ma, Z Xu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4* | 2023 |
| Benchmarking Deformable Object Manipulation with Differentiable Physics S Chen, C Yu, Y Xu, L Li, X Ma, Z Xu, D Hsu International Conference on Learning Representations (ICLR), 2023 | 4* | 2023 |
| Boosting offline reinforcement learning via data rebalancing Y Yue, B Kang, X Ma, Z Xu, G Huang, S Yan arXiv preprint arXiv:2210.09241, 2022 | 4 | 2022 |
| Hierarchical Reinforcement Learning under Mixed Observability H Nguyen, Z Yang, A Baisero, X Ma, R Platt, C Amato Workshop on the Algorithmic Foundations of Robotics (WAFR), 2022 | 2 | 2022 |
| DinerDash Gym: A Benchmark for Policy Learning in High-Dimensional Action Space S Chen, X Ma, D Hsu In IL workshop, Robotics: Science and Systems (RSS), 2020 | 2 | 2020 |
| Offline Prioritized Experience Replay Y Yue, B Kang, X Ma, G Huang, S Song, S Yan arXiv preprint arXiv:2306.05412, 2023 | 1 | 2023 |
| Improving and Benchmarking Offline Reinforcement Learning Algorithms B Kang*, X Ma*, Y Wang, Y Yue, S Yan arXiv preprint arXiv:2306.00972, 2023 | | 2023 |
| Efficient Diffusion Policies for Offline Reinforcement Learning B Kang*, X Ma*, C Du, T Pang, S Yan arXiv preprint arXiv:2305.20081, 2023 | | 2023 |
David HsuProfessor of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
