Wang Yi

Wang Yi

PhD candidate, CST, ZJNU

About me

I received my MS degree from in Applied Mathematics from CJLU, in 2021. I am currently working toward the Ph.D degree.

My research interests include graph machine learning, hypergraph computing and intelligence education.

Paper List 📰

  • Li M, Gu Y, Wang Y(通讯), Fang Y, Bai L, Zhuang X, Pietro Lio. “When hypergraph meets heterophily: New benchmark datasets and baseline” is accepted by AAAI 2025.

  • Li M, Fang Y, Wang Y(通讯), Feng H, Gu Y, Bai L, Pietro Lio. “Deep hypergraph neural networks with tight framelets” is accepted by AAAI 2025.

  • Cai T, Jiang Y, Li M, Huang C, Wang Y, Huang Q. “ML-GOOD: Towards multi-label graph out-of-distribution detection” is accepted by AAAI 2025.

  • Wang Y, Huang C, Li M, Huang Q, Wu X, Wu J. AG-Meta: Adaptive graph meta-learning via representation consistency over local subgraphs[J]. Pattern Recognition, 2024, 151: 110387.

  • Huang C, Wang Y, Jiang Y, Li M, Huang X, Wang S, Pan S, Zhou C. Flow2GNN: Flexible two-way flow message passing for enhancing GNNs beyond homophily[J]. IEEE Transactions on Cybernetics, 2024, 54(11): 6607-6618.

  • Zheng X, Wang Y(共一), Liu Y, Li M, Zhang M, Jin D, Philip S. Yu, Pan S. Graph neural networks for graphs with heterophily: A survey. arXiv preprint arXiv:2202.07082, 2022.

  • Gu Y, Wang Y(通讯), Zhang H, Wu J, Gu X. Enhancing text classification by graph neural networks with multi-granular topic-aware graph. IEEE Access, 2023, 11: 20169-20183.

  • Wang Y, Ye H, Cao F. A novel multi-discriminator deep network for image segmentation. Applied Intelligence, 2022, 52(1): 1092-1109.

  • Ye H, Wang Y, Cao F. A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer. Neural Networks, 2021, 144: 755-765.

  • Li M, Wang X, Wang Y, et al. Study-GNN: A novel pipeline for student performance prediction based on multi-topology graph neural networks[J]. Sustainability, 2022, 14(13): 7965.

  • Huang C, Zhang J, Wu X, Wang Y, Li M, Huang X. TeFNA: Text-centered fusion network with crossmodal attention for multimodal sentiment analysis[J]. Knowledge-Based Systems, 2023, 269: 110502.

  • Huang C, Yu J, Wu F, Wang Y, Chen N. Uncovering emotion sequence patterns in different interaction groups using deep learning and sequential pattern mining[J]. Journal of Computer Assisted Learning, 2024, 40(4): 1777-1790.

  • Huang Q, Chen J, Huang C, Huang X, Wang Y. Text-centered cross-sample fusion network for multimodal sentiment analysis[J]. Multimedia Systems, 2024, 30(4): 228.