| 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 | 789 | 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, 2020 | 445 | 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 | 198 | 2020 |
| Guiding Deep Molecular Optimization with Genetic Exploration S Ahn, J Kim, H Lee, J Shin Advances in Neural Information Processing Systems 33, 2020 | 89 | 2020 |
| Learning what to defer for maximum independent sets S Ahn, Y Seo, J Shin International conference on machine learning, 134-144, 2020 | 74 | 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 | 45 | 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 | 40 | 2021 |
| Self-improved retrosynthetic planning J Kim, S Ahn, H Lee, J Shin International Conference on Machine Learning, 5486-5495, 2021 | 26 | 2021 |
| Spanning tree-based graph generation for molecules S Ahn, B Chen, T Wang, L Song International Conference on Learning Representations, 2021 | 24 | 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 | 23 | 2023 |
| 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 |
| Local search gflownets M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park arXiv preprint arXiv:2310.02710, 2023 | 20 | 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 | 19 | 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, ... arXiv preprint arXiv:2306.17100, 2023 | 14 | 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 | 14 | 2021 |
| 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, 2024 | 13 | 2024 |
| Imitating graph-based planning with goal-conditioned policies J Kim, Y Seo, S Ahn, K Son, J Shin arXiv preprint arXiv:2303.11166, 2023 | 13 | 2023 |
| Sythesis of MCMC and Belief Propagation S Ahn, M Chertkov, J Shin Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2016 | 13 | 2016 |
| Learning energy decompositions for partial inference of gflownets H Jang, M Kim, S Ahn arXiv preprint arXiv:2310.03301, 2023 | 11 | 2023 |
| A deeper look at the layerwise sparsity of magnitude-based pruning J Lee, S Park, S Mo, S Ahn, J Shin arXiv preprint arXiv:2010.07611 2 (3), 2020 | 9 | 2020 |
Jinwoo ShinKAIST Endowed Chair ProfessorVerified email at kaist.ac.kr
