| Nestednet: Learning nested sparse structures in deep neural networks E Kim, C Ahn, S Oh Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 71 | 2018 |
| Deep elastic networks with model selection for multi-task learning C Ahn, E Kim, S Oh Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 50 | 2019 |
| Graph-matching-based correspondence search for nonrigid point cloud registration S Chang, C Ahn, M Lee, S Oh Computer vision and image understanding 192, 102899, 2020 | 18 | 2020 |
| Deep virtual networks for memory efficient inference of multiple tasks E Kim, C Ahn, PHS Torr, S Oh Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 12 | 2019 |
| BiasAdv: Bias-Adversarial Augmentation for Model Debiasing J Lim, Y Kim, B Kim, C Ahn, J Shin, E Yang, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 7 | 2023 |
| Auto-VirtualNet: Cost-adaptive dynamic architecture search for multi-task learning E Kim, C Ahn, S Oh Neurocomputing 442, 116-124, 2021 | 2 | 2021 |
| Incremental Learning With Adaptive Model Search and a Nominal Loss Model C Ahn, E Kim, S Oh IEEE Access 10, 16052-16062, 2022 | 1 | 2022 |
| Sample-wise Label Confidence Incorporation for Learning with Noisy Labels C Ahn, K Kim, J Baek, J Lim, S Han Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | | 2023 |
| Growing a Brain with Sparsity-Inducing Generation for Continual Learning H Jin, G Kim, C Ahn, E Kim Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | | 2023 |
| BiasAdv: Bias-Adversarial Augmentation for Model Debiasing-Supplementary Material J Lim, Y Kim, B Kim, C Ahn, J Shin, E Yang, S Han | | |
