| Augmentation-free self-supervised learning on graphs N Lee, J Lee, C Park Proceedings of the AAAI conference on artificial intelligence 36 (7), 7372-7380, 2022 | 168 | 2022 |
| Heterogeneous graph learning for multi-modal medical data analysis S Kim, N Lee, J Lee, D Hyun, C Park Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 5141-5150, 2023 | 19 | 2023 |
| Relational self-supervised learning on graphs N Lee, D Hyun, J Lee, C Park Proceedings of the 31st ACM International Conference on Information …, 2022 | 18 | 2022 |
| Conditional graph information bottleneck for molecular relational learning N Lee, D Hyun, GS Na, S Kim, J Lee, C Park International Conference on Machine Learning, 18852-18871, 2023 | 14 | 2023 |
| Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning J Lee, S Kim, D Hyun, N Lee, Y Kim, C Park Bioinformatics 39 (6), btad342, 2023 | 12 | 2023 |
| Grafn: Semi-supervised node classification on graph with few labels via non-parametric distribution assignment J Lee, Y Oh, Y In, N Lee, D Hyun, C Park Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 9 | 2022 |
| Self-supervised graph representation learning via positive mining N Lee, J Lee, C Park Information Sciences 611, 476-493, 2022 | 7 | 2022 |
| Task-equivariant graph few-shot learning S Kim, J Lee, N Lee, W Kim, S Choi, C Park Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 2 | 2023 |
| Single-cell RNA-seq data imputation using feature propagation S Yun, J Lee, C Park ICML 2023 Workshop on Computational Biology, 2023 | 2 | 2023 |
| Single-cell RNA sequencing data imputation using bi-level feature propagation J Lee, S Yun, Y Kim, T Chen, M Kellis, C Park Briefings in Bioinformatics 25 (3), bbae209, 2024 | | 2024 |
Chanyoung ParkKAIST在 kaist.ac.kr 的电子邮件经过验证
