| A cluster-based oversampling algorithm combining SMOTE and k-means for imbalanced medical data Z Xu, D Shen, T Nie, Y Kou, N Yin, X Han Information Sciences 572, 574-589, 2021 | 171 | 2021 |
| How would stance detection techniques evolve after the launch of chatgpt? B Zhang, D Ding, L Jing, G Dai, N Yin arXiv preprint arXiv:2212.14548, 2022 | 138 | 2022 |
| A survey of graph neural networks in real world: Imbalance, noise, privacy and ood challenges W Ju, S Yi, Y Wang, Z Xiao, Z Mao, H Li, Y Gu, Y Qin, N Yin, S Wang, ... arXiv preprint arXiv:2403.04468, 2024 | 63 | 2024 |
| CoCo: A coupled contrastive framework for unsupervised domain adaptive graph classification N Yin, L Shen, M Wang, L Lan, Z Ma, C Chen, XS Hua, X Luo International Conference on Machine Learning, 40040-40053, 2023 | 59* | 2023 |
| Dynamic hypergraph convolutional network N Yin, F Feng, Z Luo, X Zhang, W Wang, X Luo, C Chen, XS Hua 2022 IEEE 38th International Conference on Data Engineering (ICDE), 1621-1634, 2022 | 50 | 2022 |
| Investigating chain-of-thought with chatgpt for stance detection on social media B Zhang, X Fu, D Ding, H Huang, G Dai, N Yin, Y Li, L Jing arXiv preprint arXiv:2304.03087, 2023 | 45 | 2023 |
| OMG: Towards effective graph classification against label noise N Yin, L Shen, M Wang, X Luo, Z Luo, D Tao IEEE Transactions on Knowledge and Data Engineering 35 (12), 12873-12886, 2023 | 41 | 2023 |
| Deep imbalanced learning for multimodal emotion recognition in conversations T Meng, Y Shou, W Ai, N Yin, K Li IEEE Transactions on Artificial Intelligence, 2024 | 40 | 2024 |
| Deal: An unsupervised domain adaptive framework for graph-level classification N Yin, L Shen, B Li, M Wang, X Luo, C Chen, Z Luo, XS Hua Proceedings of the 30th ACM International Conference on Multimedia, 3470-3479, 2022 | 40 | 2022 |
| Dynamic spiking graph neural networks N Yin, M Wang, Z Chen, G De Masi, H Xiong, B Gu Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16495 …, 2024 | 35 | 2024 |
| A comprehensive survey on multi-modal conversational emotion recognition with deep learning Y Shou, T Meng, W Ai, N Yin, K Li arXiv preprint arXiv:2312.05735, 2023 | 34 | 2023 |
| Messages are never propagated alone: Collaborative hypergraph neural network for time-series forecasting N Yin, L Shen, H Xiong, B Gu, C Chen, XS Hua, S Liu, X Luo IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (4), 2333-2347, 2023 | 34 | 2023 |
| Graph information bottleneck for remote sensing segmentation Y Shou, W Ai, T Meng, N Yin arXiv preprint arXiv:2312.02545, 2023 | 27 | 2023 |
| CZL-CIAE: CLIP-driven Zero-shot Learning for Correcting Inverse Age Estimation Y Shou, W Ai, T Meng, N Yin, K Li arXiv preprint arXiv:2312.01758, 2023 | 27 | 2023 |
| Merging Multi-Task Models via Weight-Ensembling Mixture of Experts A Tang, L Shen, Y Luo, N Yin, L Zhang, D Tao ICML, 2024 | 26 | 2024 |
| Adversarial representation with intra-modal and inter-modal graph contrastive learning for multimodal emotion recognition Y Shou, T Meng, W Ai, N Yin, K Li arXiv preprint arXiv:2312.16778, 2023 | 25 | 2023 |
| Der-gcn: Dialogue and event relation-aware graph convolutional neural network for multimodal dialogue emotion recognition W Ai, Y Shou, T Meng, N Yin, K Li arXiv preprint arXiv:2312.10579, 2023 | 24 | 2023 |
| Sa-gda: Spectral augmentation for graph domain adaptation J Pang, Z Wang, J Tang, M Xiao, N Yin Proceedings of the 31st ACM international conference on multimedia, 309-318, 2023 | 23 | 2023 |
| DREAM: Dual structured exploration with mixup for open-set graph domain adaption N Yin, M Wang, Z Chen, L Shen, H Xiong, B Gu, X Luo The Twelfth International Conference on Learning Representations, 2024 | 21 | 2024 |
| Revisiting multi-modal emotion learning with broad state space models and probability-guidance fusion Y Shou, T Meng, F Zhang, N Yin, K Li arXiv preprint arXiv:2404.17858, 2024 | 19 | 2024 |
