| Reciprocity in directed hypergraphs: measures, findings, and generators S Kim, M Choe, J Yoo, K Shin Data Mining and Knowledge Discovery 37 (6), 2330-2388, 2023 | 19 | 2023 |
| A survey on hypergraph neural networks: An in-depth and step-by-step guide S Kim, SY Lee, Y Gao, A Antelmi, M Polato, K Shin Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 18 | 2024 |
| Four-set hypergraphlets for characterization of directed hypergraphs H Moon, H Kim, S Kim, K Shin arXiv preprint arXiv:2311.14289, 2023 | 16 | 2023 |
| Prototype-based explanations for graph neural networks (student abstract) YM Shin, SW Kim, EB Yoon, WY Shin Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 13047 …, 2022 | 14 | 2022 |
| Classification of edge-dependent labels of nodes in hypergraphs M Choe, S Kim, J Yoo, K Shin Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 12 | 2023 |
| Hypeboy: Generative self-supervised representation learning on hypergraphs S Kim, S Kang, F Bu, SY Lee, J Yoo, K Shin arXiv preprint arXiv:2404.00638, 2024 | 11 | 2024 |
| How transitive are real-world group interactions?-measurement and reproduction S Kim, F Bu, M Choe, J Yoo, K Shin Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 11 | 2023 |
| Sign is not a remedy: Multiset-to-multiset message passing for learning on heterophilic graphs L Liang, S Kim, K Shin, Z Xu, S Pan, Y Qi arXiv preprint arXiv:2405.20652, 2024 | 10 | 2024 |
| Datasets, tasks, and training methods for large-scale hypergraph learning S Kim, D Lee, Y Kim, J Park, T Hwang, K Shin Data mining and knowledge discovery 37 (6), 2216-2254, 2023 | 10 | 2023 |
| Page: Prototype-based model-level explanations for graph neural networks YM Shin, SW Kim, WY Shin IEEE transactions on pattern analysis and machine intelligence, 2024 | 9 | 2024 |
| Feature distribution on graph topology mediates the effect of graph convolution: Homophily perspective SY Lee, S Kim, F Bu, J Yoo, J Tang, K Shin arXiv preprint arXiv:2402.04621, 2024 | 9 | 2024 |
| Slade: Detecting dynamic anomalies in edge streams without labels via self-supervised learning J Lee, S Kim, K Shin Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 3 | 2024 |
| Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy S Kim, SY Lee, F Bu, S Kang, K Kim, J Yoo, K Shin Advances in Neural Information Processing Systems 37, 95931-95962, 2024 | 1 | 2024 |
| Towards Better Utilization of Multiple Views for Bundle Recommendation K Kim, S Kim, G Lee, K Shin Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 1 | 2024 |
| FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer D Hwang, H Kim, S Kim, K Shin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
Kijung ShinAssociate Professor, KAISTEmail yang diverifikasi di kaist.ac.kr