| Physics-informed machine learning: A survey on problems, methods and applications Z Hao, S Liu, Y Zhang, C Ying, Y Feng, H Su, J Zhu arXiv preprint arXiv:2211.08064, 2022 | 104 | 2022 |
| Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling H Chen, C Lu, C Ying, H Su, J Zhu ICLR 2023, 2022 | 68 | 2022 |
| Gnot: A general neural operator transformer for operator learning Z Hao, Z Wang, H Su, C Ying, Y Dong, S Liu, Z Cheng, J Song, J Zhu ICML 2023, 2023 | 60 | 2023 |
| Towards safe reinforcement learning via constraining conditional value-at-risk C Ying, X Zhou, H Su, D Yan, N Chen, J Zhu IJCAI 2022, 2022 | 28 | 2022 |
| GSmooth: Certified robustness against semantic transformations via generalized randomized smoothing Z Hao, C Ying, Y Dong, H Su, J Song, J Zhu ICML 2022, 2022 | 23 | 2022 |
| The robodrive challenge: Drive anytime anywhere in any condition L Kong, S Xie, H Hu, Y Niu, WT Ooi, BR Cottereau, LX Ng, Y Ma, W Zhang, ... arXiv preprint arXiv:2405.08816, 2024 | 17 | 2024 |
| A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs S Liu, Z Hao, C Ying, H Su, J Zhu, Z Cheng NeurIPS 2022, 2022 | 17 | 2022 |
| Understanding adversarial attacks on observations in deep reinforcement learning Y Qiaoben, C Ying, X Zhou, H Su, J Zhu, B Zhang Science China Information Sciences 67 (5), 1-15, 2024 | 12 | 2024 |
| Strategically-timed state-observation attacks on deep reinforcement learning agents Y Qiaoben, X Zhou, C Ying, J Zhu ICML 2021 Workshop on Adversarial Machine Learning, 2021 | 11 | 2021 |
| Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients Z Hao, C Ying, H Su, J Zhu, J Song, Z Cheng ICLR 2023, 2022 | 9 | 2022 |
| Task Aware Dreamer for Task Generalization in Reinforcement Learning C Ying, Z Hao, X Zhou, H Su, S Liu, D Yan, J Zhu arXiv preprint arXiv:2303.05092, 2023 | 7* | 2023 |
| NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data S Liu, Z Hao, C Ying, H Su, Z Cheng, J Zhu ICML 2023, 2023 | 5 | 2023 |
| DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training Z Hao, C Su, S Liu, J Berner, C Ying, H Su, A Anandkumar, J Song, J Zhu ICML 2024, 2024 | 4 | 2024 |
| Consistent attack: Universal adversarial perturbation on embodied vision navigation C Ying, Y Qiaoben, X Zhou, H Su, W Ding, J Ai Pattern Recognition Letters 168, 57-63, 2023 | 3 | 2023 |
| On the Reuse Bias in Off-Policy Reinforcement Learning C Ying, Z Hao, X Zhou, H Su, D Yan, J Zhu IJCAI 2023, 2022 | 2 | 2022 |
| PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning C Ying, Z Hao, X Zhou, X Xu, H Su, X Zhang, J Zhu arXiv preprint arXiv:2405.14073, 2024 | 1 | 2024 |
| Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning H Tan, S Liu, K Ma, C Ying, X Zhang, H Su, J Zhu ICML 2024, 2024 | | 2024 |
| MVE: Multi-View Enhancer for Robust Bird’s Eye View Object Detection C Kang, X Zhou, C Ying, W Shang, X Wei, Y Dong | | |
| Cross-Modal Transformers for Robust Multi-Modal BEV Detection C Kang, X Zhou, C Ying, W Shang, X Wei, Y Dong | | |
| Analysis of Alignment Phenomenon in Simple Teacher-student Networks with Finite Width H Zhu, C Ying, S Zuo | | |
Jun ZhuProfessor of Computer Science, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
