Corpus ID: 235694416

Root and community inference on the latent growth process of a network using noisy attachment models

@inproceedings{Crane2021RootAC,
  title={Root and community inference on the latent growth process of a network using noisy attachment models},
  author={Harry Crane and Min Xu},
  year={2021}
}
We introduce the PAPER (Preferential Attachment Plus Erdős–Rényi) model for random networks, where we let a random network G be the union of a preferential attachment (PA) tree T and additional Erdős–Rényi (ER) random edges. The PA tree component captures the fact that real world networks often have an underlying growth/recruitment process where vertices and edges are added sequentially, while the ER component can be regarded as random noise. Given only a single snapshot of the final network G… Expand

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