| Refine myself by teaching myself: Feature refinement via self-knowledge distillation M Ji, S Shin, S Hwang, G Park, IC Moon Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 139 | 2021 |
| Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation D Kim, S Shin, K Song, W Kang, IC Moon arXiv preprint arXiv:2106.05527, 2021 | 98* | 2021 |
| Abc: Auxiliary balanced classifier for class-imbalanced semi-supervised learning H Lee, S Shin, H Kim Advances in Neural Information Processing Systems 34, 7082-7094, 2021 | 85 | 2021 |
| Counterfactual fairness with disentangled causal effect variational autoencoder H Kim, S Shin, JH Jang, K Song, W Joo, W Kang, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8128-8136, 2021 | 54 | 2021 |
| Neutralizing gender bias in word embedding with latent disentanglement and counterfactual generation S Shin, K Song, JH Jang, H Kim, W Joo, IC Moon arXiv preprint arXiv:2004.03133, 2020 | 28 | 2020 |
| From noisy prediction to true label: Noisy prediction calibration via generative model HS Bae*, S Shin*, B Na, JH Jang, K Song, IC Moon International Conference on Machine Learning, 1277-1297, 2022 | 22 | 2022 |
| Loss-Curvature Matching for Dataset Selection and Condensation S Shin*, H Bae*, D Shin, W Joo, IC Moon International Conference on Artificial Intelligence and Statistics, 8606-8628, 2023 | 18 | 2023 |
| Generalized gumbel-softmax gradient estimator for various discrete random variables W Joo, D Kim, S Shin, IC Moon arXiv preprint arXiv:2003.01847, 2020 | 14 | 2020 |
| Forecasting the Concentration of Particulate Matter in the Seoul Metropolitan Area Using a Gaussian Process Model J Jang, S Shin, H Lee, IC Moon Sensors 2020 20 (3845), https://doi.org/10.3390/s20143845, 2020 | 12 | 2020 |
| Bivariate Beta-LSTM K Song, JH Jang, S Shin, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5818-5825, 2020 | 10 | 2020 |
| Frequency Domain-based Dataset Distillation D Shin*, S Shin*, IC Moon arXiv preprint arXiv:2311.08819, 2023 | 7 | 2023 |
| Evaluation of optimal scene time interval for out-of-hospital cardiac arrest using a deep neural network SJ Shin, HS Bae, HJ Moon, GW Kim, YS Cho, DW Lee, DK Jeong, HJ Kim, ... The American Journal of Emergency Medicine 63, 29-37, 2023 | 3 | 2023 |
| Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior Y Cho, HS Bae, S Shin, YD Youn, W Joo, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 38 (10), 11552 …, 2024 | 2 | 2024 |
| Neural posterior regularization for likelihood-free inference D Kim, K Song, S Shin, W Kang, IC Moon, W Joo arXiv preprint arXiv:2102.07770, 2021 | 2* | 2021 |
| FEWER: federated weight recovery Y Shin, G Lee, S Shin, S Yun, I Moon Proceedings of the 1st Workshop on Distributed Machine Learning, 1-6, 2020 | 2 | 2020 |
| Adversarial likelihood-free inference on black-box generator D Kim, W Joo, S Shin, K Song, IC Moon arXiv preprint arXiv:2004.05803, 2020 | 2 | 2020 |
| Current Calculation Simulation Model for Smartgrid-based Energy Distribution System Operation HS Bae, S Shin, IC Moon, JW Bae Journal of the Korea Society for Simulation 30 (1), 113-126, 2021 | 1 | 2021 |
| Unknown Domain Inconsistency Minimization for Domain Generalization S Shin, HS Bae, B Na, YY Kim, IC Moon arXiv preprint arXiv:2403.07329, 2024 | | 2024 |
| Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning HS Bae, S Shin, B Na, IC Moon arXiv preprint arXiv:2403.02690, 2024 | | 2024 |
| Improving Group-based Robustness and Calibration via Ordered Risk and Confidence Regularization S Shin, B Na, HS Bae, JH Jang, H Kim, K Song, Y Cho, I Moon ICML 2022: Workshop on Spurious Correlations, Invariance and Stability, 2022 | | 2022 |
Il-Chul MoonAssociate Professor, Department of Industrial and Systems Engineering, KAIST在 kaist.ac.kr 的电子邮件经过验证
