| 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 | 831 | 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 | 486 | 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 | 228 | 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 | 95 | 2020 |
| Learning what to defer for maximum independent sets S Ahn, Y Seo, J Shin International conference on machine learning, 134-144, 2020 | 86 | 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 | 55 | 2022 |
| 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 | 43 | 2021 |
| 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 | 33 | 2023 |
| Self-improved retrosynthetic planning J Kim, S Ahn, H Lee, J Shin International Conference on Machine Learning, 5486-5495, 2021 | 31 | 2021 |
| Local search gflownets M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park arXiv preprint arXiv:2310.02710, 2023 | 29 | 2023 |
| Spanning tree-based graph generation for molecules S Ahn, B Chen, T Wang, L Song International Conference on Learning Representations, 2021 | 27 | 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 | 23 | 2020 |
| 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, ... arXiv preprint arXiv:2306.17100, 2023 | 21 | 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 | 21 | 2021 |
| Learning energy decompositions for partial inference of gflownets H Jang, M Kim, S Ahn arXiv preprint arXiv:2310.03301, 2023 | 18 | 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 | 16 | 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 | 15 | 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 | 14 | 2023 |
| Synthesis of MCMC and belief propagation SS Ahn, M Chertkov, J Shin Advances in Neural Information Processing Systems 29, 2016 | 13 | 2016 |
| Holistic Molecular Representation Learning via Multi-view Fragmentation S Kim, J Nam, J Kim, H Lee, S Ahn, J Shin Transactions on Machine Learning Research, 2024 | 10* | 2024 |
