Kun Guo

Membership Uncertainty-Aware Overlapping Community Detection with Adaptive Cluster Number Estimation

Ling Wu, Xiaoyue Chen, Bin Dai, Yingjie Yang et autres

cn, gb (code pays fourni par la source)

Multi-Layer Heterophilic Graph Representation Learning with Relation Consistency Preservation

Ling Wu, Weijun Chen, Xinyu Li, Kun Guo

cn (code pays fourni par la source)

Straggler-Aware Dynamic Selection for Federated Learning

Haiqing Zhu, Haiyan Zhan, Qishan Zhang, Bin Lin et autres

cn (code pays fourni par la source)

A Federated Split Autoencoder for Privacy-Preserving Non-IID Graph Learning

Kun Guo, Kui Gao, Qingqing Huang, Yuting Liang et autres

Federated graph neural networks (Federated GNNs) have gained increasing attention in academia and industry owing to their ability to train graph learning models in a collaborative manner while complying with the growing stringency of privacy protection regulations. In practice, participants’ local graphs …

cn, hk (code pays fourni par la source)

FIT: Enhancing multimodal knowledge graph completion via fine-grained interaction and TriConvTransformer

Jingbin Wang, Zhibo Zheng, Yuhong Deng, Zeyuan Lin et autres

cn (code pays fourni par la source)

Community detection in attributed networks based on deep attention autoencoder with block diagonal subspace constraint

Ling Wu, Shuai Guo, Ziqi Cai, Jianguo Chen et autres

cn, gb (code pays fourni par la source)

Unsupervised Federated Learning on Non-IID Graphs via Contrastive Encoding and Cluster Centroid Sampling

Kui Gao, Kun Guo, Di Chai, Kai Chen

Federated graph learning (FGL) has attracted significant attention for enabling privacy-preserving collaborative model training based on multiple participants’ local graphs. However, a node’s neighbors in one participant’s local graph may be distributed across the local graphs of other participants, resulting in topological …

cn, hk (code pays fourni par la source)

Professor

Jingbin Wang, Zeyuan Lin, Yang Lin, Jiaxiang Yang et autres

cn (code pays fourni par la source)

Linear-time attributed graph clustering via collaborative learning of adaptive anchors

Ling Wu, Qishan Zhang, Zhao Kang, Kun Guo

cn (code pays fourni par la source)

Federated trajectory clustering based on multi-feature similarity calculation

Kun Guo, Xinglong Hu, Zhiyu Zhang, Chuyu Liu et autres

cn (code pays fourni par la source)

Variability and Influencing Factors of the Convective Boundary Layer Height Over the Tibetan Plateau

Yao Dai, Qian Huang, Zijun Wang, Kun Guo et autres

Abstract Convective boundary layer height (CBLH) is an essential parameter of the boundary layer climatology, which is associated with the intensity of turbulence mixing. Radiosonde data derived from the "Sino-Japanese Center for Cooperation on Meteorological Disasters" (JICA) during three intensive observation periods …

cn (code pays fourni par la source)

Capturing Global Structural Features and Global Temporal Dependencies in Dynamic Social Networks Using Graph Convolutional Networks for Enhanced Analysis

Ling Wu, Binbin Li, Kun Guo, Qishan Zhang

Modeling and analysis of complex social networks is an important topic in social computing. Graph convolutional networks (GCNs) are widely used for learning social network embeddings and social network analysis. However, real-world complex social networks, such as Facebook and Math, exhibit significant …

cn (code pays fourni par la source)