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näkemys - Rumor Source Detection
Contagion Origins: Maximum-Likelihood Estimation in Spreading Models
Probabilistic approach for rumor source detection using maximum likelihood estimation in spreading models.
Unraveling Contagion Origins: Maximum-Likelihood Estimation in Markovian Spreading Models
Effective maximum-likelihood estimation for identifying the source of contagion in networks.
GIN-SD: Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion
Proposing GIN-SD framework for rumor source detection in graphs with incomplete nodes.
Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion
The author introduces a novel framework, GIN-SD, to address the challenge of rumor source detection in graphs with incomplete nodes. By leveraging positional encoding and attentive fusion, the model aims to distinguish incomplete nodes and focus on those with higher information transmission capacity.
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