科研项目
(1) 国家自然科学基金委员会, 地区科学基金项目, 62266041, 基于多粒度临床信息表达的疾病诊断相关分组技术研究, 2023-01-01 至 2026-12-31,参与
(2) 国家自然科学基金委员会,面上项目, 72174152, 基于深度学习的社交平台用户情绪危机全过程动态管理模式的构建及效果评价, 2022-01-01至2025-12-31,参与
(3) 国家自然科学基金委员会, 青年项目, 62006009，基于深度网络嵌入的大规模属性网络社团发现研究, 2021-01至2023-12,主持
(4) 北京市自然科学基金委, 青年项目, 4204085, 基于社区优化深度表示的半监督属性网络划分方法, 2020-01至2021-12,主持
(5) 中国博士后科学基金委员会, 面上项目, 2019M650407, 大规模属性网络半监督社区发现研究, 2019-06至2020-12,主持
国家自然科学基金委员会,面上项目, 61876016, 动态属性网络随机块模型及其应用研究, 2019-01至2022-12,参与
代表性研究成果
(1) Li Y, Lin X, Jia C, et al. Adversarially deep interative-fused embedding clustering via joint self-supervised networks. Neurocomputing, 2024, 601: 128205.
(2) Li Y, Chu Z, Jia C, et al. SAMGAT: Structure-aware multilevel graph attention networks for automatic rumor detection. PeerJ Comput. Sci.10: e2200 (2024).
(3) Zu B,Cao T, Li Y, et al. SwinT-SRNet: Swin transformer with image super-resolution reconstruction network for pollen images classification, Engineering Applications of Artificial Intelligence, 2024, 133
(4) Li Y, Kang J, Li X, et al.Automated Multi-scale Contrastive Learning with Sample-Awareness for Graph lassification.APWeb/WAIM (3) 2024: 145-160
(5) Li Y, Wang W, Wei J, et al.Community-aware graph embedding via multi-level attribute integration.Knowledge and Information Systems,2023, 12(65):5635-5655.
(6) Zu B, Li Y, Li J, et al. Cascaded Convolution-based Transformer with Densely Connected Mechanism for Spectral–Spatial Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 2023, doi: 10.1109/TGRS.2023.3275871.2023.
(7) Feng W, Li Y, Li B, et al. BiMGCL: rumor detection via bi-directional multi-level graph contrastive learning, PeerJ Computer Science, 2023, 9(e1659).
(8) Li Y,Wang W,Ma G,et al. Community-enhanced Contrastive Siamese networks for Graph Representation Learning,the 16th International Conference on Knowledge Science, Engineering and Management (KSEM),Guangzhou, China, 2023.8.16-2023.8.18,2023.
(9) Li Y, Liu Y, Wei J, et al. General Community Detection in Attributed Networks with Consistent-Module Constrained Nonnegative Matrix Factorization.Wireless Communications and Mobile Computing, 2022,1-12.
(10) Li Y, Fu Y, Su H, et al. Adaptively attribute-enhanced graph embedding via deep clustering constraints, the 10th International Conference on Computing and Pattern Recognition (ICCPR), Shanghai, China, October 15-17, 2021.
(11) 李亚芳, 梁烨, 冯韦玮, 祖宝开, 康玉健. 基于社区优化的深度网络嵌入方法. 计算机应用, 2021, 41(7): 1956-1963.
(12) Li Y, Jia C, Kong X, et al. Locally weighted fusion of structural and attribute information in graph clustering. IEEE Transactions on Cybernetics, 2019, 4(1): 247-260.
(13) 洪敏,贾彩燕,李亚芳,于剑.样本加权的多视图聚类算法.计算机研究与发展,2019,56(8):1677-1685.
(14) Li Y, Jia C,Li J, et al. Enhanced semi-supervised community detection with active node and link selection. Physica A: Statistical Mechanics and Its Applications, 2018, 510: 219-232.
(15) Li Y, Kong X, Jia C, et al. Uncertain graph clustering with node attributes, 10th Asian Conference on Machine Learning(ACML), Beijing, China, 2018.11.14-11.16.
(16) Qin Y, Jia C, Li Y.Community detection using nonnegative matrix factorization with orthogonal constraint, the 8thInternational Conference on Advanced Computational Intelligence (ICACI), 49-54, Chiang Mai,Thailand, 2016.2.14-2.16.
(17) Li Y, Jia C, Yu J. A parameter-free community detection method based on centrality and dispersion of nodes in complex networks. Physica A: Statistical Mechanics and its Applications, 2015, 438(C): 321-334.
(18) 李亚芳; 储志华.一种基于结构感知图注意力网络的谣言检测方法，中国，202311698099.2
(19) 李亚芳, 王文博, 王宏远, 祖宝开. 基于图聚类优化的孪生网络对比表示学习方法及装置, 202210583382.X
李亚芳, 王思博. 社区发现方法、电子设备、存储介质以及程序产品, 2021-9-18, 中国, 202111110715.9
