| Knowledge transfer for deep reinforcement learning with hierarchical experience replay H Yin, S Pan Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 95 | 2017 |
| Learning behavior patterns from video: A data-driven framework for agent-based crowd modeling J Zhong, W Cai, L Luo, H Yin Proceedings of the 2015 International Conference on Autonomous Agents and …, 2015 | 50 | 2015 |
| Interactive scenario generation for mission‐based virtual training L Luo, H Yin, W Cai, M Lees, S Zhou Computer Animation and Virtual Worlds 24 (3-4), 345-354, 2013 | 30 | 2013 |
| Mitigating forgetting in online continual learning with neuron calibration H Yin, P Li Advances in Neural Information Processing Systems 34, 10260-10272, 2021 | 27 | 2021 |
| Design and evaluation of a data-driven scenario generation framework for game-based training L Luo, H Yin, W Cai, J Zhong, M Lees IEEE Transactions on Computational Intelligence and AI in Games 9 (3), 213-226, 2016 | 23 | 2016 |
| A review of interactive narrative systems and technologies: a training perspective L Luo, W Cai, S Zhou, M Lees, H Yin Simulation 91 (2), 126-147, 2015 | 23 | 2015 |
| Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation H Yin, D Li, X Li, P Li Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9466-9473, 2020 | 21 | 2020 |
| A data-driven approach for online adaptation of game difficulty H Yin, L Luo, W Cai, YS Ong, J Zhong 2015 IEEE conference on computational intelligence and games (CIG), 146-153, 2015 | 14 | 2015 |
| Towards a data‐driven approach to scenario generation for serious games L Luo, H Yin, W Cai, M Lees, NB Othman, S Zhou Computer Animation and Virtual Worlds 25 (3-4), 393-402, 2014 | 14 | 2014 |
| Mission-based scenario modeling and generation for virtual training L Luo, H Yin, J Zhong, W Cai, M Lees, S Zhou Proceedings of the AAAI Conference on Artificial Intelligence and …, 2013 | 9 | 2013 |
| Reinforcement Learning with Efficient Active Feature Acquisition H Yin, Y Li, SJ Pan, C Zhang, S Tschiatschek arXiv preprint arXiv:2011.00825, 2020 | 7 | 2020 |
| Hashing over predicted future frames for informed exploration of deep reinforcement learning H Yin, J Chen, SJ Pan arXiv preprint arXiv:1707.00524, 2017 | 6 | 2017 |
| Sequential Generative Exploration Model for Partially Observable Reinforcement Learning H Yin, J Chen, SJ Pan, S Tschiatschek Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10700 …, 2021 | 5 | 2021 |
| Causal Discovery with Flow-based Conditional Density Estimation S Ren, H Yin, M Sun, P Li 2021 IEEE International Conference on Data Mining (ICDM), 1300-1305, 2021 | 4 | 2021 |
| Learning to Selectively Learn for Weakly Supervised Paraphrase Generation with Model-based Reinforcement Learning H Yin, D Li, P Li Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 3 | 2022 |
| Data-Driven Dynamic Adaptation Framework for Multi-agent Training Game H Yin, L Luo, W Cai, J Zhong 2015 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2015 | 2 | 2015 |
| Crowd-level Abnormal Behavior Detection via Multi-scale Motion Consistency Learning L Luo, Y Li, H Yin, S Xie, R Hu, W Cai Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8984-8992, 2023 | 1 | 2023 |
| Partially-observed sequential variational auto encoder C Zhang, LI Yingzhen, S TSCHIATSCHEK, H Yin, J Kim US Patent App. 17/002,771, 2021 | 1 | 2021 |
| Distributional Meta-Gradient Reinforcement Learning H Yin, YAN Shuicheng, Z Xu The Eleventh International Conference on Learning Representations, 2023 | | 2023 |
| CASA: Bridging the Gap between Policy Improvement and Policy Evaluation with Conflict Averse Policy Iteration C Xiao, H Shi, J Fan, S Deng, H Yin arXiv preprint arXiv:2105.03923, 2021 | | 2021 |
Wentong CaiProfessor of Computer Science, Nanyang Technological UniversityBestätigte E-Mail-Adresse bei ntu.edu.sg
