Meta-learning with a geometry-adaptive preconditioner S Kang, D Hwang, M Eo, T Kim, W Rhee Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 23 | 2023 |
Vne: An effective method for improving deep representation by manipulating eigenvalue distribution J Kim, S Kang, D Hwang, J Shin, W Rhee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 19 | 2023 |
Learning ECG representations for multi-label classification of cardiac abnormalities J Suh, J Kim, E Lee, J Kim, D Hwang, J Park, J Lee, J Park, SY Moon, ... 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 16 | 2021 |
Aid-purifier: A light auxiliary network for boosting adversarial defense D Hwang, E Lee, W Rhee Neurocomputing 541, 126251, 2023 | 14 | 2023 |
Statistical characteristics of deep representations: An empirical investigation D Choi, K Lee, D Hwang, W Rhee International Conference on Artificial Neural Networks, 43-55, 2021 | 3 | 2021 |
Towards a Better Evaluation of Out-of-Domain Generalization D Hwang, S Kang, M Eo, J Kim, W Rhee arXiv preprint arXiv:2405.19703, 2024 | | 2024 |
Enhancing Contrastive Learning with Efficient Combinatorial Positive Pairing J Kim, D Hwang, E Lee, J Suh, J Kim, W Rhee arXiv preprint arXiv:2401.05730, 2024 | | 2024 |
GAML: geometry-aware meta-learning via a fully adaptive preconditioner S Kang, D Hwang, M Eo, T Kim, W Rhee | | |