| Self-Supervised Time-Series Anomaly Detection Using Learnable Data Augmentation K Choi, J Yi, J Mok, S Yoon arXiv preprint arXiv:2406.12260, 2024 | | 2024 |
| On the powerfulness of textual outlier exposure for visual ood detection S Park, J Mok, D Jung, S Lee, S Yoon Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Large-scale lifelong learning of in-context instructions and how to tackle it J Mok, J Do, S Lee, T Taghavi, S Yu, S Yoon Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 11 | 2023 |
| Autosnn: Towards energy-efficient spiking neural networks B Na, J Mok, S Park, D Lee, H Choe, S Yoon International Conference on Machine Learning, 16253-16269, 2022 | 58 | 2022 |
| Anti-adversarially manipulated attributions for weakly supervised semantic segmentation and object localization J Lee, E Kim, J Mok, S Yoon IEEE transactions on pattern analysis and machine intelligence 46 (3), 1618-1634, 2022 | 17 | 2022 |
| Demystifying the neural tangent kernel from a practical perspective: Can it be trusted for neural architecture search without training? J Mok, B Na, JH Kim, D Han, S Yoon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 19* | 2022 |
| Reducing information bottleneck for weakly supervised semantic segmentation J Lee, J Choi, J Mok, S Yoon Advances in neural information processing systems 34, 27408-27421, 2021 | 133 | 2021 |
| Accelerating neural architecture search via proxy data B Na, J Mok, H Choe, S Yoon arXiv preprint arXiv:2106.04784, 2021 | 19 | 2021 |
| Variance-stationary differentiable NAS H Choe, B Na, J Mok, S Yoon architecture 3 (10), 16-20, 2021 | 3 | 2021 |
| AdvRush: Searching for adversarially robust neural architectures J Mok, B Na, H Choe, S Yoon Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 37 | 2021 |
| Reduce, Reuse, and Recycle: Navigating Test-Time Adaptation with OOD-Contaminated Streams J Mok, J Lee, S Lee, S Yoon | | |
