| Pure transformers are powerful graph learners J Kim, TD Nguyen, S Min, S Cho, M Lee, H Lee, S Hong arXiv preprint arXiv:2207.02505, 2022 | 112 | 2022 |
| Equivariant Hypergraph Neural Networks J Kim, S Oh, S Cho, S Hong arXiv preprint arXiv:2208.10428, 2022 | 12 | 2022 |
| Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning S Cha, S Cho, D Hwang, S Hong, M Lee, T Moon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 8 | 2023 |
| Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers S Cha, S Cho, D Hwang, H Lee, T Moon, M Lee arXiv preprint arXiv:2301.11578, 2023 | 7 | 2023 |
| Practical correlated topic modeling and analysis via the rectified anchor word algorithm M Lee, S Cho, D Bindel, D Mimno Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 7 | 2019 |
| Grouping-matrix based Graph Pooling with Adaptive Number of Clusters SM Ko, S Cho, DW Jeong, S Han, M Lee, H Lee arXiv preprint arXiv:2209.02939, 2022 | 3 | 2022 |
| Using spectral characterization to identify healthcare-associated infection (HAI) patients for clinical contact precaution J Cui, S Cho, M Kamruzzaman, M Bielskas, A Vullikanti, BA Prakash Scientific Reports 13 (1), 16197, 2023 | 2 | 2023 |
| Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost S Cho, S Min, J Kim, M Lee, H Lee, S Hong arXiv preprint arXiv:2210.15541, 2022 | 2 | 2022 |
| Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning S Cho, S Cho, S Park, H Lee, H Lee, M Lee arXiv preprint arXiv:2309.04082, 2023 | | 2023 |
| 3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation S Cho, DW Jeong, SM Ko, J Kim, S Han, S Hong, H Lee, M Lee arXiv preprint arXiv:2309.04062, 2023 | | 2023 |
| Mixed-Curvature Transformers for Graph Representation Learning S Cho, S Cho, S Park, H Lee, H Lee, M Lee | | 2023 |
| On-the-fly Rectification for Robust Large-Vocabulary Topic Inference M Lee, S Cho, K Dong, D Bindel, D Mimno International Conference on Machine Learning (ICML), 2021 | | 2021 |
