| Differentiable meta-learning model for few-shot semantic segmentation P Tian, Z Wu, L Qi, L Wang, Y Shi, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12087 …, 2020 | 76 | 2020 |
| Libfewshot: A comprehensive library for few-shot learning W Li, Z Wang, X Yang, C Dong, P Tian, T Qin, J Huo, Y Shi, L Wang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 42 | 2023 |
| Consistent meta-regularization for better meta-knowledge in few-shot learning P Tian, W Li, Y Gao IEEE Transactions on Neural Networks and Learning Systems 33 (12), 7277-7288, 2021 | 36 | 2021 |
| Can we improve meta-learning model in few-shot learning by aligning data distributions? P Tian, H Yu Knowledge-Based Systems 277, 110800, 2023 | 9 | 2023 |
| An adversarial meta-training framework for cross-domain few-shot learning P Tian, S Xie IEEE Transactions on Multimedia 25, 6881-6891, 2022 | 7 | 2022 |
| Improving meta-learning model via meta-contrastive loss P Tian, Y Gao Frontiers of Computer Science 16 (5), 165331, 2022 | 5 | 2022 |
| An efficient deep reinforcement learning algorithm for solving imperfect information extensive-form games L Meng, Z Ge, P Tian, B An, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 5823-5831, 2023 | 2 | 2023 |
| Consistent MetaReg: alleviating intra-task discrepancy for better meta-knowledge P Tian, L Qi, S Dong, Y Shi, Y Gao Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 2 | 2021 |
| Deep FTRL-ORW: An Efficient Deep Reinforcement Learning Algorithm for Solving Imperfect Information Extensive-Form Games L Meng, Z Ge, P Tian, B An, Y Gao | 1 | 2023 |
| Modeling rationality: Toward better performance against unknown agents in sequential games Z Ge, S Yang, P Tian, Z Chen, Y Gao IEEE Transactions on Cybernetics, 2022 | 1 | 2022 |
| Improving the generalization of meta-learning on unseen domains via adversarial shift P Tian, Y Gao arXiv preprint arXiv:2107.11056, 2021 | 1 | 2021 |
| A novel image-specific transfer approach for prostate segmentation in MR images P Tian, L Qi, Y Shi, L Zhou, Y Gao, D Sheri 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 1 | 2018 |
| DDMA: Discrepancy-Driven Multi-agent Reinforcement Learning C Li, Y Hu, P Tian, S Dong, Y Gao Pacific Rim International Conference on Artificial Intelligence, 91-105, 2022 | | 2022 |
Yinghuan Shi（史颖欢）Nanjing UniversityVerified email at nju.edu.cn
