A Regularization-adaptive Non-negative Latent Factor Analysis-based Model For Recommender Systems. - Jiufang Chen; Xin Luo 001; MengChu Zhou (ICHMS, 2020)

Siamese Generative Adversarial Predicting Network for Extremely Sparse Data in Recommendation System. - Qingxian Wang 001; Renjian Zhang; Kangkang Ma; Bo Chen; Jiufang Chen; Xiaoyu Shi 001 (ISPA/BDCloud/SocialCom/SustainCom, 2021)

Hyper-parameter-evolutionary latent factor analysis for high-dimensional and sparse data from recommender systems. - Jiufang Chen; Ye Yuan 014; Tao Ruan; Jia Chen; Xin Luo 001 (Neurocomputing, 2021)

Adaptive Latent Factor Analysis via Generalized Momentum-Incorporated Particle Swarm Optimization. - Jiufang Chen; Ye Yuan 014 (ICNSC, 2022)

A Neighbor-Induced Graph Convolution Network for Undirected Weighted Network Representation. - Jiufang Chen; Ye Yuan 014 (SMC, 2023)

Pseudo Gradient-Adjusted Particle Swarm Optimization for Accurate Adaptive Latent Factor Analysis. - Xin Luo 001; Jiufang Chen; Ye Yuan 014; Zidong Wang 001 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

SDGNN: Symmetry-Preserving Dual-Stream Graph Neural Networks. - Jiufang Chen; Ye Yuan 014; Xin Luo 001 (IEEE CAA J. Autom. Sinica, 2024)

A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data. - Jiufang Chen; Kechen Liu; Xin Luo 001; Ye Yuan 014; Khaled Sedraoui; Yusuf Al-Turki 001; MengChu Zhou (IEEE CAA J. Autom. Sinica, 2024)

Enhancing graph convolutional networks with an efficient k-hop neighborhood approach. - Jiufang Chen; Xin Luo 001; Ye Yuan 014; Zidong Wang 001 (Inf. Fusion, 2025)