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 | 262 | 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 | 109 | 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 | 8 | 2024 |
Recasting continual learning as sequence modeling S Lee, J Son, G Kim Advances in Neural Information Processing Systems 36, 70433-70452, 2023 | 6 | 2023 |
Learning to continually learn with the Bayesian principle S Lee, H Jeon, J Son, G Kim arXiv preprint arXiv:2405.18758, 2024 | 4* | 2024 |