Uncertainty-based continual learning with adaptive regularization H Ahn, S Cha, D Lee, T Moon Advances in neural information processing systems 32, 2019 | 217 | 2019 |
Fair feature distillation for visual recognition S Jung, D Lee, T Park, T Moon Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 75 | 2021 |
Continual learning of micro-Doppler signature-based human activity classification D Lee, H Park, T Moon, Y Kim IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021 | 10 | 2021 |
Swift: Swin 4d fmri transformer P Kim, J Kwon, S Joo, S Bae, D Lee, Y Jung, S Yoo, J Cha, T Moon Advances in Neural Information Processing Systems 36, 42015-42037, 2023 | 7 | 2023 |
Issues for Continual Learning in the Presence of Dataset Bias D Lee, S Jung, T Moon AAAI Bridge Program on Continual Causality, 92-99, 2023 | 1 | 2023 |
Continual Learning in the Presence of Spurious Correlation D Lee, S Jung, T Moon arXiv preprint arXiv:2303.11863, 2023 | 1 | 2023 |
SwiFT: Swin 4D fMRI Transformer P Yongho Kim, J Kwon, S Joo, S Bae, D Lee, Y Jung, S Yoo, J Cha, ... arXiv e-prints, arXiv: 2307.05916, 2023 | | 2023 |
Supplementary Materials for Fair Feature Distillation for Visual Recognition S Jung, D Lee, T Park, T Moon Learning, 1, 2020 | | 2020 |
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline D Lee, S Jung, T Moon The Twelfth International Conference on Learning Representations, 0 | | |
Supplementary Materials for Uncertainty-regularized Continual Learning with Adaptive Regularization H Ahn, S Cha, D Lee, T Moon | | |