| Torchattacks: A pytorch repository for adversarial attacks H Kim arXiv preprint arXiv:2010.01950, 2020 | 231 | 2020 |
| Understanding catastrophic overfitting in single-step adversarial training H Kim, W Lee, J Lee Proceedings of the AAAI Conference on Artificial Intelligence, 35(9), 2020 | 105 | 2020 |
| Graddiv: Adversarial robustness of randomized neural networks via gradient diversity regularization S Lee, H Kim, J Lee IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 2645-2651, 2022 | 46 | 2022 |
| Compact class-conditional domain invariant learning for multi-class domain adaptation W Lee, H Kim, J Lee Pattern Recognition 112, 107763, 2021 | 14 | 2021 |
| Generating transferable adversarial examples for speech classification H Kim, J Park, J Lee Pattern Recognition 137, 109286, 2023 | 11 | 2023 |
| Exploring the effect of multi-step ascent in sharpness-aware minimization H Kim, J Park, Y Choi, W Lee, J Lee arXiv preprint arXiv:2302.10181, 2023 | 10 | 2023 |
| Stability analysis of sharpness-aware minimization H Kim, J Park, Y Choi, J Lee arXiv preprint arXiv:2301.06308, 2023 | 8 | 2023 |
| Bridged adversarial training H Kim, W Lee, S Lee, J Lee Neural Networks 167, 266-282, 2023 | 7 | 2023 |
| Differentially Private Sharpness-Aware Training J Park, H Kim, Y Choi, J Lee International Conference on Machine Learning 202, 27204-27224, 2023 | 4 | 2023 |
| Variational cycle-consistent imputation adversarial networks for general missing patterns W Lee, S Lee, J Byun, H Kim, J Lee Pattern Recognition 129, 108720, 2022 | 4 | 2022 |
| Fantastic robustness measures: the secrets of robust generalization H Kim, J Park, Y Choi, J Lee Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Fast sharpness-aware training for periodic time series classification and forecasting J Park, H Kim, Y Choi, W Lee, J Lee Applied Soft Computing 144, 110467, 2023 | 3* | 2023 |
| Exploring diverse feature extractions for adversarial audio detection Y Choi, J Park, J Lee, H Kim IEEE Access 11, 2351-2360, 2023 | 3 | 2023 |
| Fair sampling in diffusion models through switching mechanism Y Choi, J Park, H Kim, J Lee, S Park Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 21995 …, 2024 | 2 | 2024 |
| Comment on transferability and input transformation with additive noise H Kim, J Park, J Lee arXiv preprint arXiv:2206.09075, 2022 | 1 | 2022 |
| Are Self-Attentions Effective for Time Series Forecasting? D Kim, J Park, J Lee, H Kim arXiv preprint arXiv:2405.16877, 2024 | | 2024 |
| Sliced Wasserstein adversarial training for improving adversarial robustness W Lee, S Lee, H Kim, J Lee Journal of Ambient Intelligence and Humanized Computing, 1-14, 2024 | | 2024 |
| Evaluating practical adversarial robustness of fault diagnosis systems via spectrogram-aware ensemble method H Kim, S Lee, J Lee, W Lee, Y Son Engineering Applications of Artificial Intelligence 130, 107980, 2024 | | 2024 |
| Outside the (Black) Box: Explaining Risk Premium via Interpretable Machine Learning H Ko, H Kim, J Lee Available at SSRN, 2024 | | 2024 |
| Multi-Factor Model with Time-Varying Volatility: A Multi-Task Learning Approach B Son, H Kim, J Lee Available at SSRN 4840857, 0 | | |
Jaewook LeeProfessor of Industrial Engineering, Seoul National University在 snu.ac.kr 的电子邮件经过验证
