| 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 | 20 | 2022 |
| 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 | 18 | 2022 |
| 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, 2023 | 15 | 2023 |
| CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification XL Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua The 40th International Conference on Machine Learning (ICML), 2023 | 13* | 2023 |
| Messages Are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-series Forecasting XL N Yin, L Shen, H Xiong, B Gu, C Chen, XS Hua, S Liu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 9 | 2023 |
| Deep imbalanced learning for multimodal emotion recognition in conversations T Meng, Y Shou, W Ai, N Yin, K Li arXiv preprint arXiv:2312.06337, 2023 | 6 | 2023 |
| A focally discriminative loss for unsupervised domain adaptation D Sun, M Wang, X Ma, T Zhang, N Yin, W Yu, Z Luo Neural Information Processing: 28th International Conference, ICONIP 2021 …, 2021 | 6 | 2021 |
| 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 | 5 | 2023 |
| SA-GDA: Spectral Augmentation for Graph Domain Adaptation J Pang, Z Wang, J Tang, M Xiao, N Yin ACMMM, 2023 | 5 | 2023 |
| Generic structure extraction with bi-level optimization for graph structure learning N Yin, Z Luo Entropy 24 (9), 1228, 2022 | 4 | 2022 |
| Asymmetrically decentralized federated learning Q Li, M Zhang, N Yin, Q Yin, L Shen arXiv preprint arXiv:2310.05093, 2023 | 2 | 2023 |
| 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 | 1 | 2024 |
| 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 | 1 | 2024 |
| 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, 2023 | 1 | 2023 |
| Entity-aware biaffine attention for constituent parsing X Bai, N Yin, X Zhang, X Wang, Z Luo Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 1 | 2021 |
| Continuous Spiking Graph Neural Networks N Yin, M Wan, L Shen, HL Patel, B Li, B Gu, H Xiong arXiv preprint arXiv:2404.01897, 2024 | | 2024 |
| Merging Multi-Task Models via Weight-Ensembling Mixture of Experts A Tang, L Shen, Y Luo, N Yin, L Zhang, D Tao arXiv preprint arXiv:2402.00433, 2024 | | 2024 |
| Continual Learning From a Stream of APIs E Yang, Z Wang, L Shen, N Yin, T Liu, G Guo, X Wang, D Tao arXiv preprint arXiv:2309.00023, 2023 | | 2023 |
| Simultaneously Learning Syntactic Dependency and Semantics Reasonability for Relation Extraction X Wang, N Yin, X Zhang, X Bai, Z Luo The International Conference on Image, Vision and Intelligent Systems …, 2022 | | 2022 |
| Graph-PDE: Coupled ODE Structure for Graph Neural Networks N Yin, Z Chen, M Wang, L Shen, G De Masi, H Xiong, B Gu | | |
