| Exploration in deep reinforcement learning: From single-agent to multiagent domain J Hao, T Yang, H Tang, C Bai, J Liu, Z Meng, P Liu, Z Wang IEEE Transactions on Neural Networks and Learning Systems, 2023 | 90* | 2023 |
| Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning C Bai, L Wang, Z Yang, Z Deng, A Garg, P Liu, Z Wang International Conference on Learning representations (ICLR), 2022 | 57 | 2022 |
| Survey on Sparse Reward in Deep Reinforcement Learning W Yang, C Bai, C Cai, Y Zhao, P Liu 计算机科学 47 (3), 182-191, 2020 | 29* | 2020 |
| Principled Exploration via Optimistic Bootstrapping and Backward Induction C Bai, L Wang, L Han, J Hao, A Garg, P Liu, Z Wang International Conference on Machine Learning (ICML), 2021 | 27 | 2021 |
| Guided Goal Generation for Hindsight Multi-Goal Reinforcement Learning C Bai, P Liu, W Zhao, X Tang Neurocomputing 359, 353-367, 2019 | 19 | 2019 |
| RORL: Robust Offline Reinforcement Learning via Conservative Smoothing R Yang, C Bai, X Ma, Z Wang, C Zhang, L Han Neural Information Processing Systems (NeurIPS), 2022 | 16 | 2022 |
| Dynamic Bottleneck for Robust Self-Supervised Exploration C Bai, L Wang, L Han, A Garg, J Hao, P Liu, Z Wang Neural Information Processing Systems (NeurIPS), 2021 | 16 | 2021 |
| Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning S Qiu, L Wang, C Bai, Z Yang, Z Wang International Conference on Machine Learning (ICML), 18168-18210, 2022 | 12 | 2022 |
| Addressing Hindsight Bias in Multi-Goal Reinforcement Learning C Bai, L Wang, Y Wang, Z Wang, R Zhao, C Bai, P Liu IEEE Transactions on Cybernetics, 2021 | 11 | 2021 |
| Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning C Bai, P Liu, K Liu, L Wang, Y Zhao, L Han, Z Wang IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 | 10 | 2021 |
| Generating Attentive Goals for Prioritized Hindsight Reinforcement Learning P Liu, C Bai, Y Zhao, C Bai, W Zhao, X Tang Knowledge-Based Systems 203, 106140, 2020 | 10 | 2020 |
| Active Sampling for Deep Q-learning Based on TD-error Adaptive Correction C Bai, P Liu, W Zhao, X Tang 计算机研究与发展 56 (2), 262-280, 2019 | 7* | 2019 |
| Score: Spurious correlation reduction for offline reinforcement learning Z Deng, Z Fu, L Wang, Z Yang, C Bai, Z Wang, J Jiang arXiv preprint arXiv:2110.12468, 2021 | 6 | 2021 |
| Monotonic Quantile Network for Worst-Case Offline Reinforcement Learning C Bai, T Xiao, Z Zhu, L Wang, F Zhou, A Garg, B He, P Liu, Z Wang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 5 | 2022 |
| Research on Autonomous Driving Methods Based on Computer Vision and Deep Learning C Bai Harbin Institute of Technology, 2017 | 5 | 2017 |
| Obtaining Accurate Estimated Action Values in Categorical Distributional Reinforcement Learning Y Zhao, P Liu, C Bai, W Zhao, X Tang Knowledge-Based Systems 194, 105511, 2020 | 2 | 2020 |
| Privileged Knowledge Distillation for Sim-to-Real Policy Generalization H He, C Bai, H Lai, L Wang, W Zhang arXiv preprint arXiv:2305.18464, 2023 | 1 | 2023 |
| Robust Quadrupedal Locomotion via Risk-Averse Policy Learning J Shi, C Bai, H He, L Han, D Wang, B Zhao, X Li, X Li arXiv preprint arXiv:2308.09405, 2023 | | 2023 |
| Self-Supervised Imitation for Offline Reinforcement Learning With Hindsight Relabeling X Yu, C Bai, C Wang, D Yu, CLP Chen, Z Wang IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023 | | 2023 |
| Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning H He, C Bai, K Xu, Z Yang, W Zhang, D Wang, B Zhao, X Li arXiv preprint arXiv:2305.18459, 2023 | | 2023 |
Lingxiao WangNorthwestern UniversityVerified email at u.northwestern.edu
