[Jul 22nd 2020] LabMeeting: Partial Distance Correlation for Exploring Dependence Between Similarity Networks

Federica Baccini (University of Florence)

Jul 22, 2020 – 11:00 AM
Conference Meeting
Description

Similarity network fusion is a tool that aggregates the information coming from a multiplex network into a unique layer through a cross diffusion process.
However, the process itself does not allow to infer which layer has the major impact in the determination of the topology of the resulting
network.
In this talk, the use of distance correlation and, in turn, partial distance correlation is proposed for individuating which layer is the
most relevant in the determination of the final network structure. Finally, an application to networks of scholarly journals is presented.

 |  Category: Seminars