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Motif-based community detection in heterogeneous multilayer networks
Multilayer networks composed of intralayer edges and interlayer edges are an important type of complex networks. Considering the heterogeneity of...
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Multi-view Heterogeneous Graph Neural Networks for Node Classification
Recently, with graph neural networks (GNNs) becoming a powerful technique for graph representation, many excellent GNN-based models have been...
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Testing structural balance theories in heterogeneous signed networks
The abundance of data about social relationships allows the human behavior to be analyzed as any other natural phenomenon. Here we focus on balance...
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Similarity enhancement of heterogeneous networks by weighted incorporation of information
In many real-world datasets, different aspects of information are combined, so the data is usually represented as heterogeneous graphs whose nodes...
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Heterogeneous Graph Neural Networks
As a powerful graph representation technique based on deep learning, graph neural networks (GNNs) have shown superior performance and attracted...
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Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks
In order to help investors understand the credit status of target corporations and reduce investment risks, the corporate credit rating model has...
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Random networks with heterogeneous reciprocity
Users of social networks display diversified behavior and online habits. For instance, a user’s tendency to reply to a post can depend on the user...
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Configuration optimization for heterogeneous time-sensitive networks
Time-Sensitive Networking (TSN) collectively defines a set of protocols and standard amendments that enhance IEEE 802.1Q Ethernet nodes with...
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Bounded intra-layer synchronization of multilayer heterogeneous networks without external controllers
Multilayer network models with heterogeneous nodes characterize complex network in the reality to the best effect, and bounded synchronization has...
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Learning on heterogeneous graph neural networks with consistency-based augmentation
Heterogeneous Graph Neural Networks(HGNNs), as an effective tool for mining heterogeneous graphs, have achieved remarkable performance on series of...
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Laplacian renormalization group for heterogeneous networks
The renormalization group is the cornerstone of the modern theory of universality and phase transitions and it is a powerful tool to scrutinize...
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Set-based visualization and enhancement of embedding results for heterogeneous multi-label networks
Heterogeneous networks are ubiquitous in the real-world, such as social networks and brain cell networks. Network embedding techniques have emerged...
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Variable Hybrid Action Space Deep Q-Networks for Optimal Power Allocation and User Association in Heterogeneous Networks
Heterogeneous networks (HetNets) are essential in contemporary wireless communication networks as they help operators address challenges related to...
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Network political education optimization based on heterogeneous cellular networks and deep learning
In order to meet the needs of wireless communications for higher data rates and wider coverage, this article has specially formulated a...
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RW-HeCo: A random walk and network centrality based graph neural network for community detection in heterogeneous networks
Real-world networks often consist of different types of nodes, which leads to the creation of heterogeneous graphs. Most studies on heterogeneous...
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Cooperation and Integration in 6G Heterogeneous Networks Resource Allocation and Networking
To provide ubiquitous and various services, 6G networks tend to be more comprehensive and multidimensional by integrating current terrestrial...
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Network alignment and link prediction using event-based embedding in aligned heterogeneous dynamic social networks
People are associated with multiple social networks to enjoy the exclusive services provided by each. Such users may be well established in some...
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Turing pattern of an SIRI model on large-scale homogeneous and heterogeneous networks
Taking into account the spatial flow and relapse behaviors, this paper establishes a network-organized reaction-diffusion system for disease...
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Global asymptotic synchronization for coupled heterogeneous complex networks via Laplace transform approach
In this work, the global asymptotic synchronization (GAS) is investigated for the drive-response coupled heterogeneous complex networks (DRCHCNS). By...
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Protein function annotation based on heterogeneous biological networks
BackgroundAccurate annotation of protein function is the key to understanding life at the molecular level and has great implications for biomedicine...
