| 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 | 69 | 2021 |
| Augmented variational autoencoders for collaborative filtering with auxiliary information W Lee, K Song, IC Moon Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 68 | 2017 |
| 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 |
| Blackvip: Black-box visual prompting for robust transfer learning C Oh, H Hwang, H Lee, YT Lim, G Jung, J Jung, H Choi, K Song Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 39 | 2023 |
| Lada: Look-ahead data acquisition via augmentation for deep active learning YY Kim, K Song, JH Jang, IC Moon Advances in Neural Information Processing Systems 34, 22919-22930, 2021 | 37 | 2021 |
| Sequential recommendation with relation-aware kernelized self-attention M Ji, W Joo, K Song, YY Kim, IC Moon Proceedings of the AAAI conference on artificial intelligence 34 (04), 4304-4311, 2020 | 35 | 2020 |
| Hierarchical Context enabled Recurrent Neural Network for Recommendation K Song, M Ji, S Park, IC Moon Thirty-Third AAAI Conference on Artificial Intelligence, 2019 | 35 | 2019 |
| Score matching model for unbounded data score D Kim, S Shin, K Song, W Kang, IC Moon arXiv preprint arXiv:2106.05527 7, 2021 | 30 | 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 |
| Deep generative positive-unlabeled learning under selection bias B Na, H Kim, K Song, W Joo, YY Kim, IC Moon Proceedings of the 29th acm international conference on information …, 2020 | 25 | 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 |
| Unknown-aware domain adversarial learning for open-set domain adaptation JH Jang, B Na, DH Shin, M Ji, K Song, IC Moon Advances in Neural Information Processing Systems 35, 16755-16767, 2022 | 19 | 2022 |
| Learning fair representation via distributional contrastive disentanglement C Oh, H Won, J So, T Kim, Y Kim, H Choi, K Song Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 19 | 2022 |
| Geodesic multi-modal mixup for robust fine-tuning C Oh, J So, H Byun, YT Lim, M Shin, JJ Jeon, K Song Advances in Neural Information Processing Systems 36, 2024 | 18 | 2024 |
| Hierarchically clustered representation learning SJ Shin, K Song, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5776-5783, 2020 | 14 | 2020 |
| Implicit kernel attention K Song, Y Jung, D Kim, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9713-9721, 2021 | 13 | 2021 |
| State prediction of high-speed ballistic vehicles with Gaussian process IC Moon, K Song, SH Kim, HL Choi International Journal of Control, Automation and Systems 16, 1282-1292, 2018 | 13 | 2018 |
| Bivariate beta-LSTM K Song, JH Jang, S jae Shin, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5818-5825, 2020 | 10 | 2020 |
| Towards calibrated robust fine-tuning of vision-language models C Oh, M Kim, H Lim, J Park, E Jeong, ZQ Cheng, K Song arXiv preprint arXiv:2311.01723, 2023 | 7 | 2023 |
| Adversarial dropout for recurrent neural networks S Park, K Song, M Ji, W Lee, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4699-4706, 2019 | 7 | 2019 |
Il-Chul MoonAssociate Professor, Department of Industrial and Systems Engineering, KAIST在 kaist.ac.kr 的电子邮件经过验证
