Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification N Ma, J Bu, J Yang, Z Zhang, C Yao, Z Yu, S Zhou, X Yan Proceedings of the 29th ACM International Conference on Information …, 2020 | 60* | 2020 |
Learning Spatial-Preserved Skeleton Representations for Few-Shot Action Recognition N Ma, H Zhang, X Li, S Zhou, Z Zhang, J Wen, H Li, J Gu, J Bu ECCV 2022, 2022 | 24 | 2022 |
Context-guided entropy minimization for semi-supervised domain adaptation N Ma, J Bu, L Lu, J Wen, S Zhou, Z Zhang, J Gu, H Li, X Yan Neural Networks 154, 270-282, 2022 | 14 | 2022 |
Source-free semi-supervised domain adaptation via progressive Mixup N Ma, H Wang, Z Zhang, S Zhou, H Chen, J Bu Knowledge-Based Systems 262, 110208, 2023 | 12 | 2023 |
Homophily-enhanced structure learning for graph clustering M Gu, G Yang, S Zhou, N Ma, J Chen, Q Tan, M Liu, J Bu Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 6 | 2023 |
Semi-supervised hypothesis transfer for source-free domain adaptation N Ma, J Bu, L Lu, J Wen, Z Zhang, S Zhou, X Yan arXiv preprint arXiv:2107.06735, 2021 | 6 | 2021 |
Partition speeds up learning implicit neural representations based on exponential-increase hypothesis K Liu, F Liu, H Wang, N Ma, J Bu, B Han Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
Uncertainty-guided mixup for semi-supervised domain adaptation without source data N Ma, J Bu, Z Zhang, S Zhou arXiv preprint arXiv:2107.06707, 2021 | 3 | 2021 |
Structure enhanced prototypical alignment for unsupervised cross-domain node classification M Liu, Z Zhang, N Ma, M Gu, H Wang, S Zhou, J Bu Neural Networks 177, 106396, 2024 | 2 | 2024 |
Implicit Neural Distance Optimization for Mesh Neural Subdivision K Liu, N Ma, Z Wang, J Gu, J Bu, H Wang 2023 IEEE International Conference on Multimedia and Expo (ICME), 2039-2044, 2023 | 2 | 2023 |
Generalizing to Unseen Domains for Regression N Ma, F Liu, H Wang, X Zhang, H Chen, B Han, J Bu | | |
Partition Matters in Learning and Learning-to-Learn Implicit Neural Representations K Liu, F Liu, H Wang, N Ma, J Bu, B Han | | |