| Self-supervised Label Augmentation via Input Transformations H Lee, SJ Hwang, J Shin International Conference on Machine Learning, 2020 | 155* | 2020 |
| Learning What and Where to Transfer Y Jang*, H Lee*, SJ Hwang, J Shin International Conference on Machine Learning, 2019 | 116 | 2019 |
| Guiding deep molecular optimization with genetic exploration S Ahn, J Kim, H Lee, J Shin Advances in neural information processing systems 33, 12008-12021, 2020 | 44 | 2020 |
| GTA: Graph Truncated Attention for Retrosynthesis SW Seo, YY Song, JY Yang, S Bae, H Lee, J Shin, SJ Hwang, E Yang Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 531-539, 2021 | 20 | 2021 |
| Patch-Level Representation Learning for Self-Supervised Vision Transformers S Yun, H Lee, J Kim, J Shin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 17 | 2022 |
| Improving Transferability of Representations via Augmentation-Aware Self-Supervision H Lee, K Lee, K Lee, H Lee, J Shin Advances in Neural Information Processing Systems 34, 2021 | 15 | 2021 |
| Anytime Neural Prediction via Slicing Networks Vertically H Lee, J Shin arXiv preprint arXiv:1807.02609, 2018 | 15 | 2018 |
| Self-improved retrosynthetic planning J Kim, S Ahn, H Lee, J Shin International Conference on Machine Learning, 5486-5495, 2021 | 13 | 2021 |
| RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning H Lee, S Ahn, SW Seo, YY Song, E Yang, SJ Hwang, J Shin arXiv preprint arXiv:2105.00795, 2021 | 8 | 2021 |
| STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables J Nam, J Tack, K Lee, H Lee, J Shin arXiv preprint arXiv:2303.00918, 2023 | 1 | 2023 |
| Meta-Learning with Self-Improving Momentum Target J Tack, J Park, H Lee, J Lee, J Shin arXiv preprint arXiv:2210.05185, 2022 | 1 | 2022 |
| Guiding Energy-based Models via Contrastive Latent Variables H Lee, J Jeong, S Park, J Shin arXiv preprint arXiv:2303.03023, 2023 | | 2023 |
| Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning H Jang, H Lee, J Shin arXiv preprint arXiv:2303.00996, 2023 | | 2023 |
