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Cycling topic graph learning for neural topic modeling Journal article
Liu, Yanyan, Gong, Zhiguo. Cycling topic graph learning for neural topic modeling[J]. Knowledge-Based Systems, 2025, 310.
Authors:  Liu, Yanyan;  Gong, Zhiguo
Favorite | TC[Scopus]:0  IF:7.2/7.4 | Submit date：2025/01/22
Neural Topic Model  Graph Neural Networks  Wasserstein Autoencoder  Graph Attention Networks  
GraKerformer: A Transformer With Graph Kernel for Unsupervised Graph Representation Learning Journal article
Xu, Lixiang, Liu, Haifeng, Yuan, Xin, Chen, Enhong, Tang, Yuanyan. GraKerformer: A Transformer With Graph Kernel for Unsupervised Graph Representation Learning[J]. IEEE Transactions on Cybernetics, 2024, 54(12), 7320-7332.
Authors:  Xu, Lixiang;  Liu, Haifeng;  Yuan, Xin;  Chen, Enhong;  Tang, Yuanyan
Favorite | TC[WOS]:1 TC[Scopus]:2  IF:9.4/10.3 | Submit date：2024/12/05
Graph Kernel  Graph Neural Networks (Gnns)  Structural Encoding Method  Transformer  
Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation Conference paper
Cai, Jinyu, Zhang, Yunhe, Lu, Zhoumin, Guo, Wenzhong, Ng, See Kiong. Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation[C]:Association for Computing Machinery, Inc, 2024, 5537-5546.
Authors:  Cai, Jinyu;  Zhang, Yunhe;  Lu, Zhoumin;  Guo, Wenzhong;  Ng, See Kiong
Favorite | TC[Scopus]:1 | Submit date：2024/12/05
Anomaly Detection  Federated Learning  Graph Neural Networks  Unsupervised Learning  
From Cluster Assumption to Graph Convolution: Graph-Based Semi-Supervised Learning Revisited Journal article
Wang, Zheng, Ding, Hongming, Pan, Li, Li, Jianhua, Gong, Zhiguo, Yu, Philip S.. From Cluster Assumption to Graph Convolution: Graph-Based Semi-Supervised Learning Revisited[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024.
Authors:  Wang, Zheng;  Ding, Hongming;  Pan, Li;  Li, Jianhua;  Gong, Zhiguo; et al.
Favorite | TC[WOS]:2 TC[Scopus]:3  IF:10.2/10.4 | Submit date：2024/11/05
Data Mining  Graph Convolutional Neural Networks  Graph-based Semi-supervised Learning (Gssl)  
Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials Journal article
Zhao, Zirui, Li, Hai Feng. Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials[J]. ACS Applied Materials & Interfaces, 2024, 16(39), 53153-53162.
Authors:  Zhao, Zirui;  Li, Hai Feng
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:8.3/8.7 | Submit date：2024/10/10
Graph Neural Networks (Gnns)  Interface Diffusion  Material Properties Prediction  Atomic Structure Modeling  Semiconductor Interfaces  
Predicting doping strategies for ternary nickel–cobalt–manganese cathode materials to enhance battery performance using graph neural networks Journal article
Zhao, Zirui, Luo, Dong, Wu, Shuxing, Sun, Kaitong, Lin, Zhan, Li, Hai Feng. Predicting doping strategies for ternary nickel–cobalt–manganese cathode materials to enhance battery performance using graph neural networks[J]. Journal of Energy Storage, 2024, 98, 112982.
Authors:  Zhao, Zirui;  Luo, Dong;  Wu, Shuxing;  Sun, Kaitong;  Lin, Zhan; et al.
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:8.9/9.0 | Submit date：2024/08/05
Doping Strategies  Electrochemical Performance  Graph Neural Networks  Lithium-ion Batteries  Ternary Nickel–cobalt–manganese Cathode Materials  
DyGKT: Dynamic Graph Learning for Knowledge Tracing Conference paper
KE CHENG, LINZHI PENG, PENGYANG WANG, JUNCHEN YE, LEILEI SUN, BOWEN DU. DyGKT: Dynamic Graph Learning for Knowledge Tracing[C], New York, NY, USA:Association for Computing Machinery, 2024, 409-420.
Authors:  KE CHENG;  LINZHI PENG;  PENGYANG WANG;  JUNCHEN YE;  LEILEI SUN; et al.
Favorite | TC[Scopus]:1 | Submit date：2024/08/28
Dynamic Graph  Educational Data Mining  Graph Neural Networks  Knowledge Tracing  
Generalized Few-Shot Node Classification With Graph Knowledge Distillation Journal article
Wang, Jialong, Zhou, Mengting, Zhang, Shilong, Gong, Zhiguo. Generalized Few-Shot Node Classification With Graph Knowledge Distillation[J]. IEEE Transactions on Computational Social Systems, 2024.
Authors:  Wang, Jialong;  Zhou, Mengting;  Zhang, Shilong;  Gong, Zhiguo
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:4.5/4.6 | Submit date：2024/05/16
Few-shot Learning (Fsl)  Graph Neural Networks (Gnns)  Knowledge Distillation  Node Classification  
Informative Nodes Mining for Class-Imbalanced Representation Learning Journal article
Zhou, Mengting, Gong, Zhiguo. Informative Nodes Mining for Class-Imbalanced Representation Learning[J]. IEEE Transactions on Computational Social Systems, 2024.
Authors:  Zhou, Mengting;  Gong, Zhiguo
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.5/4.6 | Submit date：2024/05/16
Class Imbalanced Learning  Costs  Graph Neural Network (Gnn)  Graph Neural Networks  Node Classification  Representation Learning  Social Networking (Online)  Task Analysis  Training  Training Data  
Temporal inductive path neural network for temporal knowledge graph reasoning Journal article
Dong, Hao, Wang, Pengyang, Xiao, Meng, Ning, Zhiyuan, Wang, Pengfei, Zhou, Yuanchun. Temporal inductive path neural network for temporal knowledge graph reasoning[J]. Artificial Intelligence, 2024, 329, 104085.
Authors:  Dong, Hao;  Wang, Pengyang;  Xiao, Meng;  Ning, Zhiyuan;  Wang, Pengfei; et al.
Favorite | TC[WOS]:4 TC[Scopus]:11  IF:5.1/4.8 | Submit date：2024/05/02
Graph Neural Networks  Knowledge Graph Reasoning  Temporal Knowledge Graph  Temporal Reasoning