| A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning S Lee, J Ha, D Zhang, G Kim International Conference on Learning Representations, 2020 | 259 | 2020 |
| Improving occlusion and hard negative handling for single-stage pedestrian detectors J Noh, S Lee, B Kim, G Kim Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 108 | 2018 |
| Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation S Lee, J Ha, G Kim International Conference on Learning Representations, 2019 | 31 | 2019 |
| Recursion of Thought: A Divide-and-Conquer Approach to Multi-Context Reasoning with Language Models S Lee, G Kim Findings of the Association for Computational Linguistics (ACL), 2023 | 22 | 2023 |
| When meta-learning meets online and continual learning: A survey J Son, S Lee, G Kim IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 5 | 2024 |
| Recasting continual learning as sequence modeling S Lee, J Son, G Kim Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Learning to Continually Learn with the Bayesian Principle S Lee, H Jeon, J Son, G Kim arXiv preprint arXiv:2405.18758, 2024 | 2 | 2024 |
Gunhee KimProfessor, Seoul National UniversityEmail verificata su snu.ac.kr