| Variational information distillation for knowledge transfer S Ahn, SX Hu, A Damianou, ND Lawrence, Z Dai Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 978 | 2019 |
| Learning from failure: De-biasing classifier from biased classifier J Nam, H Cha, S Ahn, J Lee, J Shin Advances in Neural Information Processing Systems 33, 20673-20684, 2020 | 603 | 2020 |
| Layer-adaptive sparsity for the magnitude-based pruning J Lee, S Park, S Mo, S Ahn, J Shin arXiv preprint arXiv:2010.07611, 2020 | 404 | 2020 |
| 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 | 118 | 2020 |
| Learning what to defer for maximum independent sets S Ahn, Y Seo, J Shin International conference on machine learning, 134-144, 2020 | 115 | 2020 |
| Learning debiased classifier with biased committee N Kim, S Hwang, S Ahn, J Park, S Kwak Advances in Neural Information Processing Systems 35, 18403-18415, 2022 | 71 | 2022 |
| A closer look at the intervention procedure of concept bottleneck models S Shin, Y Jo, S Ahn, N Lee International Conference on Machine Learning, 31504-31520, 2023 | 59 | 2023 |
| Roma: Robust model adaptation for offline model-based optimization S Yu, S Ahn, L Song, J Shin Advances in Neural Information Processing Systems 34, 4619-4631, 2021 | 59 | 2021 |
| Rl4co: an extensive reinforcement learning for combinatorial optimization benchmark F Berto, C Hua, J Park, L Luttmann, Y Ma, F Bu, J Wang, H Ye, M Kim, ... Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and …, 2025 | 51 | 2025 |
| Local search gflownets M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park arXiv preprint arXiv:2310.02710, 2023 | 47 | 2023 |
| Self-improved retrosynthetic planning J Kim, S Ahn, H Lee, J Shin International Conference on Machine Learning, 5486-5495, 2021 | 42 | 2021 |
| Spanning tree-based graph generation for molecules S Ahn, B Chen, T Wang, L Song International Conference on Learning Representations, 2021 | 33 | 2021 |
| QTRAN++: Improved value transformation for cooperative multi-agent reinforcement learning K Son, S Ahn, RD Reyes, J Shin, Y Yi arXiv preprint arXiv:2006.12010, 2020 | 30 | 2020 |
| Learning energy decompositions for partial inference of gflownets H Jang, M Kim, S Ahn arXiv preprint arXiv:2310.03301, 2023 | 26 | 2023 |
| Bootstrapped training of score-conditioned generator for offline design of biological sequences M Kim, F Berto, S Ahn, J Park Advances in Neural Information Processing Systems 36, 67643-67661, 2023 | 24 | 2023 |
| 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 | 24 | 2021 |
| Imitating graph-based planning with goal-conditioned policies J Kim, Y Seo, S Ahn, K Son, J Shin arXiv preprint arXiv:2303.11166, 2023 | 18 | 2023 |
| Generative flows on synthetic pathway for drug design S Seo, M Kim, T Shen, M Ester, J Park, S Ahn, WY Kim arXiv preprint arXiv:2410.04542, 2024 | 17 | 2024 |
| Graph Generation with -trees Y Jang, D Kim, S Ahn arXiv preprint arXiv:2305.19125, 2023 | 17* | 2023 |
| What makes better augmentation strategies? augment difficult but not too different J Kim, D Kang, S Ahn, J Shin International Conference on Learning Representations, 2021 | 16 | 2021 |
