Rumor Source Detection

insight - Rumor Source Detection

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.

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.

Unraveling Contagion Origins: Maximum-Likelihood Estimation in Markovian Spreading Models

Effective maximum-likelihood estimation for identifying the source of contagion in networks.

Contagion Origins: Maximum-Likelihood Estimation in Spreading Models

Probabilistic approach for rumor source detection using maximum likelihood estimation in spreading models.

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