Identifying critical nodes in complex networks by graph representation learning
E Yu, D Chen, Y Fu, Y Xu - arXiv preprint arXiv:2201.07988, 2022 - arxiv.org
Because of its wide application, critical nodes identification has become an important
research topic at the micro level of network science. Influence maximization is one of the …
research topic at the micro level of network science. Influence maximization is one of the …
GNNTAL: A Novel Model for Identifying Critical Nodes in Complex Networks
H Wang, T Luo, S Yang, M Jing, J Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Identification of critical nodes is a prominent topic in the study of complex networks.
Numerous methods have been proposed, yet most exhibit inherent limitations. Traditional …
Numerous methods have been proposed, yet most exhibit inherent limitations. Traditional …
Identifying critical nodes in complex networks via graph convolutional networks
EY Yu, YP Wang, Y Fu, DB Chen, M Xie - Knowledge-Based Systems, 2020 - Elsevier
Critical nodes of complex networks play a crucial role in effective information spreading.
There are many methods have been proposed to identify critical nodes in complex networks …
There are many methods have been proposed to identify critical nodes in complex networks …
InfGCN: Identifying influential nodes in complex networks with graph convolutional networks
G Zhao, P Jia, A Zhou, B Zhang - Neurocomputing, 2020 - Elsevier
Identifying influential nodes in a complex network is very critical as complex networks are
ubiquitous. Traditional methods, such as centrality based methods and machine learning …
ubiquitous. Traditional methods, such as centrality based methods and machine learning …
Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness
Detecting critical nodes in sparse graphs is important in a variety of application domains,
such as network vulnerability assessment, epidemic control, and drug design. The critical …
such as network vulnerability assessment, epidemic control, and drug design. The critical …
Identifying critical nodes via link equations and deep reinforcement learning
P Chen, W Fan - Neurocomputing, 2023 - Elsevier
Identifying an optimal set of nodes that can maximize the spread of influence in a network is
a crucial challenge in network science. It has numerous applications such as epidemic …
a crucial challenge in network science. It has numerous applications such as epidemic …
BGN: identifying influential nodes in complex networks via backward generating networks
Identifying influential nodes in complex networks is of great significance. During recent
decades, numerous methods regarding influential nodes identification or important nodes …
decades, numerous methods regarding influential nodes identification or important nodes …
Learning to rank influential nodes in complex networks via convolutional neural networks
Identifying influential nodes is crucial for enhancing information diffusion in complex
networks. Several approaches have been proposed to find these influential nodes based on …
networks. Several approaches have been proposed to find these influential nodes based on …
Finding influential nodes in networks with community structure
Identifying influential nodes is a fundamental issue in complex networks. Several centrality
measures take advantage of various network topological properties to target the top …
measures take advantage of various network topological properties to target the top …
Identifying influential nodes based on network representation learning in complex networks
H Wei, Z Pan, G Hu, L Zhang, H Yang, X Li, X Zhou - PloS one, 2018 - journals.plos.org
Identifying influential nodes is an important topic in many diverse applications, such as
accelerating information propagation, controlling rumors and diseases. Many methods have …
accelerating information propagation, controlling rumors and diseases. Many methods have …