| Graph transformer networks S Yun, M Jeong, R Kim, J Kang, HJ Kim Advances in neural information processing systems 32, 2019 | 1051 | 2019 |
| Ranking paragraphs for improving answer recall in open-domain question answering J Lee, S Yun, H Kim, M Ko, J Kang EMNLP 2018, 2018 | 111 | 2018 |
| Neo-gnns: Neighborhood overlap-aware graph neural networks for link prediction S Yun, S Kim, J Lee, J Kang, HJ Kim Advances in Neural Information Processing Systems 34, 13683-13694, 2021 | 102 | 2021 |
| Graph Transformer Networks: Learning meta-path graphs to improve GNNs S Yun, M Jeong, S Yoo, S Lee, SY Sean, R Kim, J Kang, HJ Kim Neural Networks 153, 104-119, 2022 | 55 | 2022 |
| DyGRAIN: An Incremental Learning Framework for Dynamic Graphs S Kim, S Yun, J Kang IJCAI, 2022 | 19 | 2022 |
| SAIN: Self-Attentive Integration Network for Recommendation S Yun, R Kim, M Ko, J Kang SIGIR 2019 Conference, 2019 | 10 | 2019 |
| Deformable graph transformer J Park, S Yun, H Park, J Kang, J Jeong, KM Kim, JW Ha, HJ Kim arXiv preprint arXiv:2206.14337, 2022 | 9 | 2022 |
| Self-supervised Multimodal Graph Convolutional Network for collaborative filtering S Kim, S Yun, J Lee, G Chang, W Roh, DN Sohn, JT Lee, H Park, S Kim Information Sciences 653, 119760, 2024 | 4 | 2024 |
| Pseudo-Edge: Semi-Supervised Link Prediction with Graph Neural Networks H Seo, S Yun, B Chang, J Kang | 1 | 2022 |
