| Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction. Q Ding, S Wu, H Sun, J Guo, J Guo IJCAI 2020 (Proceedings of the Twenty-Ninth International Joint Conference …, 2020 | 159 | 2020 |
| Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL R Yang, Y Lu, W Li, H Sun, M Fang, Y Du, X Li, L Han, C Zhang ICLR 2022 (The Tenth International Conference on Learning Representations), 2022 | 54 | 2022 |
| Adaptive regularization of labels Q Ding, S Wu, H Sun, J Guo, ST Xia AAAI 2021 (The Thirty-Fifth AAAI Conference on Artificial Intelligence), 2021 | 43* | 2021 |
| Policy Continuation with Hindsight Inverse Dynamics H Sun, Z Li, X Liu, D Lin, B Zhou NeurIPS 2019 (Advances in Neural Information Processing Systems 33), 2019 | 37 | 2019 |
| The response of sediment phosphorus retention and release to reservoir operations: numerical simulation and surrogate model development Z Xu, C Yu, H Sun, Z Yang Journal of cleaner production 271, 122688, 2020 | 34 | 2020 |
| Neuro-symbolic program search for autonomous driving decision module design J Sun, H Sun, T Han, B Zhou CoRL 2020 (Conference on Robot Learning), 2020 | 29 | 2020 |
| Membership Inference Attacks against Synthetic Data through Overfitting Detection B van Breugel, H Sun, Z Qian, M van der Schaar AISTATS 2023 (The 26th International Conference on Artificial Intelligence …, 2023 | 24 | 2023 |
| Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation via Linear Reward Shaping H Sun, L Han, R Yang, X Ma, J Guo, B Zhou Advances in Neural Information Processing Systems 35, 37719-37734, 2022 | 22* | 2022 |
| Supervised Q-Learning can be a Strong Baseline for Continuous Control H Sun, Z Xu, M Fang, B Zhou NeurIPS 2022 Foundation Models for Decision Making Workshop, 2022 | 17* | 2022 |
| Physical-layer authentication based on hierarchical variational autoencoder for industrial internet of things R Meng, X Xu, B Wang, H Sun, S Xia, S Han, P Zhang IEEE Internet of Things Journal 10 (3), 2528-2544, 2022 | 16 | 2022 |
| Safe Exploration by Solving Early Terminated MDP H Sun, Z Xu, M Fang, Z Peng, J Guo, B Dai, B Zhou NeurIPS 2022 Deep RL Workshop, 2022 | 14* | 2022 |
| Novel policy seeking with constrained optimization H Sun, Z Peng, B Dai, D Lin, B Zhou NeurIPS 2022 Deep RL Workshop, 2022 | 13 | 2022 |
| Non-local policy optimization via diversity-regularized collaborative exploration Z Peng, H Sun, B Zhou arXiv preprint arXiv:2006.07781, 2020 | 13 | 2020 |
| Query-Dependent Prompt Evaluation and Optimization with Inverse Reinforcement Learning H Sun, A Hüyük, M van der Schaar ICLR 2024, 2024 | 8* | 2024 |
| Neural Laplace Control for Continuous-time Delayed Systems S Holt, A Hüyük, Z Qian, H Sun, M van der Schaar AISTATS 2023 (The 26th International Conference on Artificial Intelligence …, 2023 | 7 | 2023 |
| On the guaranteed almost equivalence between imitation learning from observation and demonstration Z Cheng, L Liu, A Liu, H Sun, M Fang, D Tao TNNLS (IEEE Transactions on Neural Networks and Learning Systems), 2021 | 7 | 2021 |
| DAUX: a Density-based Approach for Uncertainty eXplanations H Sun, B van Breugel, J Crabbe, N Seedat, M van der Schaar NeurIPS 2023 (Advances in Neural Information Processing Systems 37), 2023 | 6* | 2023 |
| Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples H Sun, A Hüyük, D Jarrett, M van der Schaar NeurIPS 2023 (Advances in Neural Information Processing Systems 37), 2023 | 6* | 2023 |
| Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond H Sun arXiv preprint arXiv:2310.06147, 2023 | 3 | 2023 |
| Unsupervised star galaxy classification with cascade variational auto-encoder H Sun, J Guo, EJ Kim, RJ Brunner arXiv preprint arXiv:1910.14056, 2019 | 3 | 2019 |
Bolei ZhouAssistant Professor at UCLA在 ucla.edu 的电子邮件经过验证
